-
Open Access Article
1 - Copy-move forgery detection techniques based on traditional methods in digital images
maryam attaie Azar MahmoodzadehImage forgery is one of the most widely used fields in image processing, which has been widely studied and studied by researchers. There are different types of digital image forgery, copy-move forgery is one of the common examples, and it is very important to recognize MoreImage forgery is one of the most widely used fields in image processing, which has been widely studied and studied by researchers. There are different types of digital image forgery, copy-move forgery is one of the common examples, and it is very important to recognize this type of forgery. In this review article, while introducing the concepts of copy-move image forgery, the steps, classification of detection methods and research bias in this field have been discussed. This article can open the way for image processing researchers in the process of detecting copy- move forgery. The authors' effort has been to explore all aspects of this process. Manuscript profile -
Open Access Article
2 - Social Spider Optimization Algorithm in Multimodal Medical Image Registration
Zahra Hossein-Nejad Mehdi NasriMedical image registration plays an important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions. Multimodal medical image registration is the process of overlapping two or more images ta MoreMedical image registration plays an important role in many clinical applications, including the detection and diagnosis of diseases, planning of therapy, guidance of interventions. Multimodal medical image registration is the process of overlapping two or more images taken from the same scene by different modalities and different sensors. Intensity-based methods are widely used in multimodal medical image registration, these techniques register different modality images that have the same content by optimal transformation. The estimation of the optimal transformation requires the optimization of a similarity metric between the images. Recently, various optimization algorithms have been presented that the selection of appropriate optimization algorithms is very important in determining the optimal transformation parameter. The Social Spider Optimization (SSO) algorithm is one of the meta-heuristic methods that prevents premature convergence. In this paper, medical image registration technique is suggested based on the SSO algorithm. The Mutual Information (MI), Normalization of Mutual Information (NMI), and Sum of Squared Differences (SSD) are used separately as cost function (objective function) and the performance of each of these functions is checked in multimodal medical image registration. The simulation results on Brain Web data set affirm Manuscript profile -
Open Access Article
3 - A Novel Fuzzy-C Means Image Segmentation Model for MRI Brain Tumor Diagnosis
Aref Safari Danial Barazandeh Seyed Ali Khalegh Pour -
Open Access Article
4 - Designing and implementing a system for Automatic recognition of Persian letters by Lip-reading using image processing methods
Masoud Barkhan Fattah Alizadeh Vafa Maihami -
Open Access Article
5 - Detecting and counting vehicles using adaptive background subtraction and morphological operators in real time systems
Lida Shahmiri Sajad Tavassoli Seyed Navid Hejazi Jouybari -
Open Access Article
6 - A method for classifying oranges based on image processing and neural networks
Hassan Rashidi Faride Esmaili Mostafa Khojastehnazhand -
Open Access Article
7 - Improving the performance of the minimum rotational image difference function method using the CMA-ES algorithm in optimal orientation
seyed vahid Lakziyan Moosarreza Shamsyeh Zahedi aghileh heydari Majid AnjidaniOrientation is a vital ability for humans and animals. Noticing the way insects orient in nature can be used to improve the orientation skills of robots. The main question of this research can be stated as follows. What kind of information do insects perceive of natural MoreOrientation is a vital ability for humans and animals. Noticing the way insects orient in nature can be used to improve the orientation skills of robots. The main question of this research can be stated as follows. What kind of information do insects perceive of natural scenes, using their visual ability, that enables them to orient and to find the direction of movement? For orientation, the minimum of rotational image difference function (MrIDF) method can be applied using panoramic image processing [1]. In MrIDF method, even with full shift, if the distance between the location of the current view image and the reference image increases, the return path cannot be correctly identified due to the increase in the difference between the two images. In this paper, we present a solution that can be used to identify the path and return angle in places far from the reference location. We also improve the efficiency the rotIDF minimum method by using the covariance matrix adaptation evolutionary strategy (CMA-ES) optimization algorithm. We show the efficiency of this method via a navigation example. The results show that finding the direction of movement through the proposed algorithm is done with sufficient accuracy and in much less time. Manuscript profile -
Open Access Article
8 - The Optimization and Modeling of the Formulation and Cooking Conditions of a Processed Analogue Cheese on the Base of UF-Feta Iranian Cheese through the Slow Cooling Method
J. Shabani H. Mirzaei S. M. Jafari M. SarfaraziIntroduction: Processed cheese is the resulted of the combination of natural cheese withdairy and non-dairy elements. A simple type and production technology of processed cheeseis based on the application of low quality cheeses with wide extent of flavor and texture tha MoreIntroduction: Processed cheese is the resulted of the combination of natural cheese withdairy and non-dairy elements. A simple type and production technology of processed cheeseis based on the application of low quality cheeses with wide extent of flavor and texture thathas resulted in the increased production of this product as a suitable substitute for the naturalcheese. The aim of this study is to optimize the replacement of milk fat with the sunflower oilat different times and temperatures of cooking through the slow cooking method concernedwith the physical properties of the processed cheese.Materials and Methods: In this study, response surface methodology (RSM) was employedto investigate the effect of vegetable oil concentration (20, 30 and 40%), cooking temperature(65, 75 and 85ᵒC) and time (5, 10 and 15 min) on the physical properties of the cheese thatconsisted of hardness, meltability and oiling-off through the slow chilling method.Results: As the vegetable oil concentration increased, the cheese hardness decreased (P<0.01)and there were no significant differences in the oiling off and meltability of the cheese. Theeffect of time and temperature of cooking was inversely related to the vegetable oilconcentration.Conclusion: The optimum conditions for the production of the processed analogue cheesewere the vegetable oil concentration of 20%, cooking temperature of 85ᵒC and time of 15 minunder which the optimum values for the hardness, meltability and oiling-off were 23.337,237.5 and 228.2% respectively. Manuscript profile -
Open Access Article
9 - Characterization of Dried Kiwi by Infrared Systems and Process Modeling
E. Aidani M. H. Haddad Khodaparast M. KashaninejadIntroduction: Modeling might be considered as a relationship between different variablesduring drying of food products and mass transfer kinetics and moisture diffusivity coefficientscan be used as useful tools for the optimal control of the process conditions that impr MoreIntroduction: Modeling might be considered as a relationship between different variablesduring drying of food products and mass transfer kinetics and moisture diffusivity coefficientscan be used as useful tools for the optimal control of the process conditions that improve thequality of the final dried product. Kiwi fruit has favorable taste and aroma and has a highnutritional value. The aim of this research work is to investigate the effect of radiation on thecharacterization of Kiwi fruit.Materials and Methods: In this study the effect of radiation lamp power at three levels of200, 250 and 300 W, at 5, 10 and 15 cm distance from sample surface on mass transferkinetics, moisture diffusion coefficients, density, color change, texture and rehydration of theKiwi were investigated.Results: The results showed that the lamp power and the distance from the sample surfacehave significant effect on moisture loss kinetics and drying time. By increasing the infraredlamp power, the weight loss is increased (61.01 %) and by increasing the infrared lamp powerfrom 200 to 300 W, the effective diffusivity coefficient has been increased from 6.25×10-10m2/s to 13.8×10-10 m2/s. The color of the samples were analyzed by image processingtechnique and the average color changes (ΔE) for 200, 250 and 300 W were 14.02, 19.09 and21.66, respectively. The average density and rehydration for dried samples were 743kg/m3and 229.18 %, respectively.Conclusion: The effect of infrared power on effective diffusivity coefficient of Kiwi wasinvestigated and found that the effective diffusivity coefficient is increased by increasing thesource of heat. The hardness of dried kiwi slices through infrared dryer was in the range of9.55-11.08 N. In the Kiwi drying process modeling as compared with other models, Pagemodel had the best match with the experimental results. Manuscript profile -
Open Access Article
10 - The Effect of Balangu Seed Gum (Lallemantia royleana) on Improving the Physicochemical, Textural and Sensory Characteristics of Sponge Cake Enriched with Pumpkin Powder
B. Ganji Vatan S.H. Hosseini GhaboosIntroduction: Pumpkin powder is used because of its high nutritional value, highly desirableflavor, sweetness and appropriate color to improve the quality of bakery products and alltypes of cakes. In this study, Balangu seed gum was used to improve the characteristics o MoreIntroduction: Pumpkin powder is used because of its high nutritional value, highly desirableflavor, sweetness and appropriate color to improve the quality of bakery products and alltypes of cakes. In this study, Balangu seed gum was used to improve the characteristics ofpumpkin cake.Materials and Methods: Firstly, the pumpkin cake batter containing different percentages ofBalangu seed gum (at four levels 0, 0.5, 1, and 1.5%) was prepared and their viscosity wasmeasured. The cakes were then cooked and the physicochemical properties including weight,ash, moisture, volume, density, crumb color, texture and sensory characteristics weremeasured.Results: Pumpkin cakes batter was a non-newtonian fluid and shear-dependent and timedependenttype. By increasing Balangu seed gum percentage in pumpkin cake formulation,the viscosity of batter increased (p<0.05). By increasing the Balangu seed gum from 0 to 1.5%, pumpkin cakes batters viscosity at shear rate of 40 s-1 ware increased from 16.93 to 32.21Pa.s (p<0.05). The moisture content and volume of cakes were increased by increasing gumpercentage (p<0.05). The increases of Balangu gum increased the brightness of cakes due toincreasing volume, in addition yellow colour of the samples decreased (p<0.05).Conclusion: The increase in gum content, the firmness of the cakes was reduced, but theamount of springness, cohesiveness and resilience of the cakes increased significantly due tothe formation of prper and soft texture by gum in the cakes (p<0.05). The L*, a* and b*indexes for sample containing 1.5 % gum were 85.25, 3.491 and 50.25, respectively. Pumpkincake containing 1.5% Balangu seed gum had significantly more acceptability than othersamples (p<0.05). Manuscript profile -
Open Access Article
11 - The Effect of Quince Powder on Rheological Properties of Batter and Physico-Chemical and Sensory Properties of Sponge Cake
F. Salehi M. Kashaninejad -
Open Access Article
12 - Segmentation of CT images of the liver with radiology based on the water-based algorithm
Mohsen AghataheriKhozani Fataneh Taghizadeh-FarahmandPurpose: The purpose of the present study is to segment the CT images of the liver with radiology based on the watershed algorithm. Materials and methods: In this study, a semi-automated method for dividing liver tumors using CT scan images has been presented. First, t MorePurpose: The purpose of the present study is to segment the CT images of the liver with radiology based on the watershed algorithm. Materials and methods: In this study, a semi-automated method for dividing liver tumors using CT scan images has been presented. First, the tumor and liver tissue is determined by the user with point selection. Then, with the help of Abpakhshan method, the three-dimensional morphology of the primary points in the tumor and liver are determined. Then, estimation of tumor and liver tissue labels is done with the method of propagation of dependent constraints. By taking the distance between the obtained labels, the tumor boundary is obtained, and finally, the final boundaries of the tumor are determined by using the edge detector. Findings: Changes in the number of initial points have little effect on the output results. In the CAP method, considering that the data estimation is done using the sampled points and estimates around these points, with any number of initial samples, the CAP method is able to produce the final results, which shows the high power of the CAP method in It is an estimate of the data. Conclusion: The use of the watershed algorithm improves the segmentation of CT images of the liver with radiology. Manuscript profile -
Open Access Article
13 - Determining Position and Orientation of 6R Robot using Image Processing
Amin Habibnejad Korayem Ensieh Niyavarani Saeed Rafee Nekoo Moharam Habibnejad -
Open Access Article
14 - Modeling of Turbulent Flow Around a Square Obstacle using a Generated Mesh by Image Processing Method
Bahador Abolpour Rahim Shamsoddini -
Open Access Article
15 - Improving the Accuracy of Detecting Cancerous Tumors Based on Deep Learning on MRI Images
Milad Ghasemi Maryam Bayati -
Open Access Article
16 - Point Target Localization and Imaging with Plane Wave using SAR
Hajar Abedi Bijan Zakeri -
Open Access Article
17 - Identification of the new and active buried salt dome evidences in the Zagros region using interferometry method of SENTINEL-1 and ASAR radar images
Ali MehrabiSalt domes are one of the most beautiful natural phenomena. Despite the outcrops of many salt domes in the Zagros region, but many of them are still buried and hidden. Due to active Zagros tectonics, the movement and ascending trend of salt domes do not stop. In this re MoreSalt domes are one of the most beautiful natural phenomena. Despite the outcrops of many salt domes in the Zagros region, but many of them are still buried and hidden. Due to active Zagros tectonics, the movement and ascending trend of salt domes do not stop. In this research, with the aim of the changes monitoring in the Earth's crust in the Zagros area, one of the new, hidden and ascending probabilistic salt domes, was identified using a radar interferometry method. For this purpose, ASAR radar images for the years 2007 and 2012 and SENTINEL-1 for the years 2014 and 2017 were used. In order to determine the amount of changes in the earth's crust, during the process of unwrapping on the images, the interference of each of the images was extracted. According to the results of the analysis of ASAR images, the growth rate of the salt dome was 1.6 centimeters per year between 2007 and 2012. While according to the interferometry images that obtained from SENTINEL-1 the rising speed of this salt dome increased between 2014 and 2017, reaching 2.9 centimeters per year. The result of this study shows that the probabilistic salt dome is active. Consequently, due to the importance of salt domes in various fields of natural resources, especially in the formation of oil reservoirs in the Zagros region, as well as more accurate identification of the subject, it is necessary to carry out special geophysical studies in this area. Manuscript profile -
Open Access Article
18 - Performance Comparison of Three Artificial Neural Network Algorithms in Identifying Seeds of Twenty Weed Species
Mohhamad reza Bagheri Mohammad Hasan Rashed Mohasel Mahmoud Reza GolzariyanThis study was conducted to investigate the efficiency of three artificial neural network algorithms employed to identify seeds of 20 weed species from their scanned images. A total of 15 features related to seed shape and size were extracted from the images using an im MoreThis study was conducted to investigate the efficiency of three artificial neural network algorithms employed to identify seeds of 20 weed species from their scanned images. A total of 15 features related to seed shape and size were extracted from the images using an image-editing program these image-extracted data were fed as inputs into three neural networks of Multilayer perceptron (MLP), RBF/GRNN/PNN Network and Generalized Feed Forward (GFF) neural network employed for seed identification purposes. RBF/GRNN/PNN network is a combined network of Radial Basic Function (RBF), General Regression Neural Network (GRNN) and Probabilistic Neural Network (PNN). After the training stage, each network was tested. The results of testing stage indicated that Generalized Feed Forward network had the highest identification accuracy (90%). This network was able to identify 8 out of twenty species by 100% accuracy. The least seed identification accuracy, using this network, was 52%. The accuracy of RBF/GRNN/PNN network was found to be 61% and this network could accurately identify only 4 species with 100% accuracy. The least precision percentage using this network was zero. The Multilayer perceptron network with 71% identification accuracy had an intermediate efficiency among the three networks. The overall results showed that GFF had the highest efficiency in identifying the studied weed seeds among the three networks. Manuscript profile -
Open Access Article
19 - Strain geometry and structural analysis of the Oshnavieh ophiolite (NW Iran): A new segment of the Neo-Tethys puzzle
Majid Niromand Mahdi Behyari Yousef Rahimsouri -
Open Access Article
20 - Detecting and Counting Pistachio Psylla Pest Using Machine Vision in Laboratory Condition
Mohammad Ghorbani Mohammadmehdi Maharlooei Kamal AhmadiPlant diseases and pest damages are one of the main factors that reduce both quality and quantity of final crops and restrict growers profit. Problems in photosynthesis and evapotranspiration may be taken place due to these pathogens. Efforts to apply chemicals or emplo MorePlant diseases and pest damages are one of the main factors that reduce both quality and quantity of final crops and restrict growers profit. Problems in photosynthesis and evapotranspiration may be taken place due to these pathogens. Efforts to apply chemicals or employing other methods for pest and disease control need precise field scouting and experts to identify the problem in a timely manner. Psylla pest is one of the most prevalent pests in pistachio orchards, which causes irreparable damage to orchards every year. In this study, the feasibility of employing machine vision to discriminate and count Pistachio Psylla was evaluated. Field data were collected from research orchards in three different time slots in summer based on pest infestation. The images were taken by various cellphone cameras with different resolutions in high and low controlled lighting conditions. The results of image-based count were compared with manual count by the expert technician in the laboratory. The effect of different light conditions and cameras with different resolutions on pest detection were evaluated by ANOVA test. There was no significant difference between manual count and digital count in high lighting conditions, but the differences in low lighting conditions were significant (p<0.05). The incorrect classification percentage values for low lighting conditions were higher than the ones obtained for high lighting conditions. This could be due to the lower quality of the images, in higher ISO values in low lighting conditions.The results showed that images taken by low-cost cameras in proper light intensity can easily replace the time-consuming and labor-intensive method of manual count. Manuscript profile -
Open Access Article
21 - Image Resolution Increasing using Segmentation
Zahra Ghanbari Vahid Ghods -
Open Access Article
22 - Image processing on images of ancient artifacts with the help of methods based on artificial intelligence
Mahyar Radak Anita Akhgar -
Open Access Article
23 - Diagnosis of brain tumor using image processing and determination of its type with RVM neural networks
elahe alipoor azar Nasser Lotfivand -
Open Access Article
24 - Optimal detection of suspected lung nodules using a novel convolution neural network
Reza Majidpourkhoei Mehdi Alilou Kambiz Majidzadeh Amin BabazadehSangar -
Open Access Article
25 - An Improved Real-Time Noise Removal Method in Video StreamBased on Pipe-and-Filter Architecture
Vahid Fazel Asl Babak Karasfi Behrooz Masoumi Mohamadreza Keyvanpor -
Open Access Article
26 - Design and Implementation of Quadrotor Guidance and Detection System Hardware for Passing Through Window Based on Machine Vision
Sahar Azizi Mohammad Menhaj Mohammad Norouzi -
Open Access Article
27 - New Approach for Approximation of Dispersivity in Porous Media
Mohammad Reza Fadaei Tehrani Raheleh Feizy Homayoun Jahanian -
Open Access Article
28 - The Application of Object- Based Image Analysis Approach for Land Use/Cover Change Modeling of Urban Growth within the City of Maragheh
Bakhtiar Fezizadeh Alireza TaheriLand-use can be considered as a combination of physical, social, cultural, economic, and informational concept of every country. In fact, the land-use maps include ways for using land for human’s different needs. Since warning land-use maps and their updates are a MoreLand-use can be considered as a combination of physical, social, cultural, economic, and informational concept of every country. In fact, the land-use maps include ways for using land for human’s different needs. Since warning land-use maps and their updates are as the most important goal in the management of lands, the use of remote sensing technology is the best way to extract the user's maps. The present study aims to employ HDR sensor with digital processing SPOT satellite images related to 2005 and satellite image obtained from the sensor of AVNIR, AlOS for 2011 to extract land use maps based on object-based image analysis approach. Accordingly, in the pre-processing step was spent on the image and in the processing phase after the detection of images, they were classified using object based advanced method. For the classification the function (the nearest neighborhood) and algorithms (hierarchical classification) were used. The method of image processing was object-based which was performed using spatial and spectral algorithms in knowledge-based manner at e-cognition software. In the next step, the validation step was performed and the accuracy of classification for 2005 was calculated to be 84 percent and for the year 2011 it was assessed to be about 81 percent. The results of this research are important for decision makers in this area for the task of regional planning and monitoring. Manuscript profile -
Open Access Article
29 - A Novel Transformation Watershed Image Segmentation Model in Digital Elevation Maps Processing
Aref Safari -
Open Access Article
30 - Robust Edge Detection Method with Subpixel Accuracy in Presence of Noise
Masoud Alidoust Mansoor Zeinali Homayoun Mahdavi-NasabEdge detection is one of the most important issues in image processing and machine vision. Edge detection in image processing is a low order process, so that the performance of the higher order processes such as object identification, segmentation and coding of images i MoreEdge detection is one of the most important issues in image processing and machine vision. Edge detection in image processing is a low order process, so that the performance of the higher order processes such as object identification, segmentation and coding of images is directly related to the efficiency of this process. The estimation of edge parameters with using gradient vector calculation is usually not accurate. Keeping the structure of edge is one of the most important problems in edge detection, especially in detecting noisy images. For practical applications that accurate edges are needed, subpixel edge detection is done. In this paper a new edge detection method based on edge figure and obtained model from neighboring pixels effect and spatial relation of image pixels is introduced. Then an iterative restoration process based on presented edge detector is suggested. The purpose of this method is to increase the accuracy in recognition of subpixel position, curvature, orientation and change in intensity in noisy images. Manuscript profile -
Open Access Article
31 - Definition of Scatterer in Electromagnetic Wave Propagation Environment Using Image Processing Based on FDTD Method
Mahmood Falah Ali Reza MalahzadehIn this paper, we implement real irregular terrain model in computer program by using image processing. We show how this approach can be used in simulation of E.M. wave propagation on irregular earth’s surface in a realistic manner. Some simulations are performed MoreIn this paper, we implement real irregular terrain model in computer program by using image processing. We show how this approach can be used in simulation of E.M. wave propagation on irregular earth’s surface in a realistic manner. Some simulations are performed for implementation of longitudinal height differences over the propagation path as PEC surface .We also describe that how this approach can be used for any boundary condition in computational space. The results observed in Snapshots of the field profiles taken at different simulation times, validates capability of this method. Manuscript profile -
Open Access Article
32 - Improvement of Industrial Radiography for Defect Detection of Oil and Gas Pipelines in Weld Regions by Image Processing
Ali Reza Karimian Monir Torabian Mohammad Reza YazdchiIndustrial Radiography is one of the oldest and most usable of non-destructive methods for studying the defects inside the weld regions of pipelines. It sounds, to increase the quality of radiographic images inside the film and to decrease the weld commentary errors. It MoreIndustrial Radiography is one of the oldest and most usable of non-destructive methods for studying the defects inside the weld regions of pipelines. It sounds, to increase the quality of radiographic images inside the film and to decrease the weld commentary errors. It is necessary to have a system or method to improve the accuracy of recognition and detection of defects in the weld regions. In this research work, by using digital image processing methods, a new method has been proposed to improve the quality of the images on radiographic films of weld regions. The proposed method has been tested by 60 pieces of radiographic films of weld regions with different quality. The results showed the proposed algorithm and method has the ability to detect the defects inside the weld regions with 100% precision for the films with high and normal quality and with 87% and 47% precisions for the films with low and very low qualities respectively. Manuscript profile -
Open Access Article
33 - تعیین اندازه گل و رنگ پوست بره های زندی با استفاده از پردازش تصویر و شبکه عصبی مصنوعی
م. خجسته کی ع.ا. اسلمی نژاد ع.ر. جعفری اروریدر این مطالعه، روشی بر مبنای استفاده از پردازش تصویر و شبکه عصبی مصنوعی برای تعیین رنگ و نوع گل پوست در بره ­های نوزاد گوسفند زندی معرفی شده است. داده­ ها از 300 بره­ نوزاد در مرکز پرورش گوسفند زندی خجیر تهران جمع ­آوری شد. در ابتدا، اندازه و شکل گل پوست Moreدر این مطالعه، روشی بر مبنای استفاده از پردازش تصویر و شبکه عصبی مصنوعی برای تعیین رنگ و نوع گل پوست در بره ­های نوزاد گوسفند زندی معرفی شده است. داده­ ها از 300 بره­ نوزاد در مرکز پرورش گوسفند زندی خجیر تهران جمع ­آوری شد. در ابتدا، اندازه و شکل گل پوست بره ­های تازه متولد شده توسط ارزیاب ­های با تجربه ثبت شد و به طور هم­زمان، چندین عکس دیجیتال از نمای جانبی هر بره گرفته شد. ویژگی­ های مربوط به اندازه گل و رنگ پوست بره­ ها از تصاویر دیجیتال با استفاده از ابزار پردازش تصویر (IPT) نرم­ افزار MATLAB استخراج شد. برای تعیین رنگ پوست، طبقه ­بندی پوست براساس اندازه گل و نیز برای برآورد اندازه گل پوست بره ­ها سه شبکه عصبی مصنوعی مجزا طراحی شد. رنگ پوست بره ­ها با استفاده از شبکه عصبی مصنوعی با دقت 100 درصد تعیین شد. دقت شبکه عصبی آموزش ­دیده برای طبقه­ بندی پوست بره ­ها بر اساس اندازه گل آنها 87/94 درصد بود. همچنین دقت شبکه عصبی سوم برای برآورد اندازه گل­ های پوست 44/98 درصد بود. همبستگی بین اندازه گل برآورد شده با استفاده از شبکه عصبی مصنوعی و اندازه گل تعیین شده توسط ارزیاب 4/96 درصد (0.01>P) بود. نتایج این مطالعه نشان داد که امکان استفاده از هوش مصنوعی به عنوان جایگزین ارزیابی انسانی در ثبت صفات پوست وجود دارد. Manuscript profile -
Open Access Article
34 - امکان سنجی تخمین وزن بدن شترهای کلکوهی با استفاده از پردازش تصاویر دیجیتال
م. خجسته کی م. کلانتر نیستانکی ز. رودباری ح. صادقی پناه ه. جواهری ع.ر. آقاشاهیهدف از این مطالعه بررسی امکان برآورد وزن شترهای کلکوهی با استفاده از پردازش تصاویر دیجیتال بود. برای این منظور، شترهای کلکوهی ماهانه در یک مزرعه خصوصی به مدت یک سال وزن می­شدند. در روز وزن­کشی، تصاویر دیجیتال از تمام شترها و از نمای جانبی آن­ها گرفته شد. این Moreهدف از این مطالعه بررسی امکان برآورد وزن شترهای کلکوهی با استفاده از پردازش تصاویر دیجیتال بود. برای این منظور، شترهای کلکوهی ماهانه در یک مزرعه خصوصی به مدت یک سال وزن می­شدند. در روز وزن­کشی، تصاویر دیجیتال از تمام شترها و از نمای جانبی آن­ها گرفته شد. این تصاویر دیجیتال در محیط نرم­افزار MATLAB پردازش شده و ویژگی­های عددی مورد نیاز هر تصویر از جمله ویژگی­های مختلف مورفولوژیکی تصاویر استخراج شد. از بین تمام ویژگی­های استخراج شده، برخی مانند طول محور اصلی، طول محور فرعی، تعداد عناصر غیر صفر (NNZ) و قطر معادل با وزن شترها ارتباط معنی­دار و بالایی داشتند (P<0.01) و از این نظر به­ عنوان ویژگی­ های مؤثر در توسعه شبکه عصبی در نظر گرفته شدند. برای برآورد وزن شترها بر اساس تصاویر دیجیتالی آن­ها از شبکه عصبی مصنوعی چند لایه که با الگوریتم پس انتشار خطا آموزش داده شده بود، استفاده شد. دقت مدل نهایی در برآورد وزن شترهای کلکوهی براساس ویژگی­ های تصویر آن­ها 99 درصد بود. ضریب همبستگی بین وزن تخمین­زده­ شده با مدل شبکه عصبی مصنوعی و وزن واقعی شترها 98 درصد و انحراف وزن تخمین­زده شده از وزن واقعی شترها 2.21 کیلوگرم بود. نتایج این تحقیق نشان داد که فناوری پردازش دیجیتال ظرفیت خوبی برای تخمین وزن شترهای کلکوهی دارد و این روش می­تواند جایگزین مناسبی برای وزن­کشی شترها با استفاده از باسکول باشد. Manuscript profile -
Open Access Article
35 - اندازهگیری خصوصیات مورفومتریکی پستان در نژادهای گوسفند دورگ و خالص
س. صادقی س. ع. رافت غ. مقدم ح. جانمحمدیتکنیک پردازش تصویر برای مقایسه خصوصیات مورفومتریکی پستان در دو جمعیت از گوسفندان دورگ شامل: قزل-آرخارمرینوس و مغانی-آرخارمرینوس و یک جمعیت از گوسفندان خالص قزل مورد استفاده قرار گرفت. بعلاوه، نتایج به دست آمده از اندازه­گیری­های مورفومتریکری پستان به عنوان متغی Moreتکنیک پردازش تصویر برای مقایسه خصوصیات مورفومتریکی پستان در دو جمعیت از گوسفندان دورگ شامل: قزل-آرخارمرینوس و مغانی-آرخارمرینوس و یک جمعیت از گوسفندان خالص قزل مورد استفاده قرار گرفت. بعلاوه، نتایج به دست آمده از اندازه­گیری­های مورفومتریکری پستان به عنوان متغیرهای مستقل در برآورد تولید شیر روزانه در مدلهای رگرسیونی مورد استفاده قرار گرفتند. ارتفاع پستان در گوسفندان قزل بیشتر از دورگ­های قزل-آرخارمرینوس و مغانی-آرخارمرینوس بود. ارتفاع مخزن چپ و راست پستان در گوسفندان مغانی-آرخارمرینوس نسبت به سایر گروه­های نامتعادلتر بود. برای پیشبینی تولید شیر روزانه در گوسفندان قزل، زاویه بین سرپستانکها، طول اتصال پستان، زاویه سرپستانک راست از محور قائم و فاصله عقب سرپستانک نسبت به سایر صفات مورفومتریکی پستان از اهمیت بیشتری برخوردار بودند. نتایج این تحقیق نشان داد که پردازش تصاویر دیجیتالی می­تواند به عنوان یک ابزار جایگزین برای شناسایی صفات بیومترک استفاده شود و صحت مشاهدات و اندازهگیریهای مورفومتریک را روی حیوانات اهلی نسبت به روشهای مرسوم بهبود ببخشد. Manuscript profile -
Open Access Article
36 - License Plate Detection Using Sobel Operator
Khosro Kamalatabar Malekshah Hossein Nematzadeh Homayun Motameni -
Open Access Article
37 - Computing of the Burnt Forest Regions Area Using Digital Image Processing
Hamidreza Gorgani Firouzjaee Hamid Hassanpour Asadollah Shahbahrami -
Open Access Article
38 - Intelligent Diabetic Retinopathy Diagnosis in Retinal Images
Marzie Zahmatkesh Ali Rafiee Majid Mazinani -
Open Access Article
39 - شناسایی گیاهان آپارتمانی بر اساس ویژگی های تصویری با کمک شبکه عصبی
نرگس قانعی قوشخانه عباس روحانی محمودرضا گلزاریان فاطمه کاظمیدر این مقاله سامانه بینایی ماشینی مبتنی بر شبکه عصبی برای شناسایی 12 گیاه آپارتمانی توسعه داده شد. از سامانه پردازش تصویر برای استخراج 41 ویژگی رنگی، بافتی و شکلی از تصاویر رو و پشت برگ گیاه استفاده گردید. ویژگی­های استخراج یافته به عنوان معیار تشخیص و و Moreدر این مقاله سامانه بینایی ماشینی مبتنی بر شبکه عصبی برای شناسایی 12 گیاه آپارتمانی توسعه داده شد. از سامانه پردازش تصویر برای استخراج 41 ویژگی رنگی، بافتی و شکلی از تصاویر رو و پشت برگ گیاه استفاده گردید. ویژگی­های استخراج یافته به عنوان معیار تشخیص و ورودی به شبکه عصبی داده شد. شبکه عصبی پرسپترون چند لایه (MLP) با الگوریتم آموزش، الگوریتم فاکتور کاهش نرخ یادگیری (BDLRF) به عنوان طبقه­بندی کننده استفاده گردید. طبقه­بندی در سه مرحله براساس قابلیت و قدرت ویژگیها در شناسایی گیاهان انجام شد. معیار قابلیت داشتن در هر مرحله با استفاده از قدرت تفکیک پذیری کلاسی گیاهان بررسی گردید. در این روش طبقه­بندی، هر مرحله نیاز به تعداد کمی از ویژگیها دارد؛ در نتیجه سرعت و دقت آن میتواند بسیار بالا باشد. نتایج نشان داد که دقت طبقه­بندی گیاهان در سه مرحله به 100% میرسد. همچنین ویژگیهای بهینه برای طبقه­بندی شامل سه مرحلهی ورودی از ویژگیهای موفولوژیکی (شکلی)، ویژگیهای رنگی HSI استخراج یافته از پشت برگ و ویژگیهای بافتی HSI استخراج یافته از پشت برگها میشود. Manuscript profile -
Open Access Article
40 - Some Physical Properties of Full-Ripe Banana Fruit (Cavendish variety)
M, Soltani R, Alimardani M, Omid -
Open Access Article
41 - تشخیص دقیق خرابی میوه در محصولات کشاورزی با استفاده از یک الگوریتم بهینه
حمیدرضا صابرکاری هدف اصلی این مقاله معرفی یک الگوریتم بهینه برای تشخیص خرابی میوه­ها در محصولات کشاورزی است. ابتدا، تصویر ورودی با استفاده از مدل ترکیبی فیلرینگ تطبیق بلوک سه­بعدی و آنالیز مولفه­های اصلی نویززدایی می­شود. سپس به منظور کاهش ابعاد تصویر و در نتیجه به More هدف اصلی این مقاله معرفی یک الگوریتم بهینه برای تشخیص خرابی میوه­ها در محصولات کشاورزی است. ابتدا، تصویر ورودی با استفاده از مدل ترکیبی فیلرینگ تطبیق بلوک سه­بعدی و آنالیز مولفه­های اصلی نویززدایی می­شود. سپس به منظور کاهش ابعاد تصویر و در نتیجه بهبود سرعت پردازش، الگوریتم بهبودیافته تبدیل کسینوسی گسسته مورد استفاده قرار می­گیرد. نهایتا الگوریتم خوشه­بندی فازی با اطلاعات مکانی بر روی تصویر فشرده شده اعمال می­شود. نتایج پیاده­سازی در محیط نرم­افزار متلب و بر اساس تصاویر جمع­آوری شده توسط نویسنده نشان می­دهد که الگوریتم پیشنهادی از قابلیت بالایی در حذف نویز برخوردار است. همچنین در این الگوریتم تشخیص نواحی خراب در میوه در مقایسه با سایر روش­های متداول با دقت بالاتری صورت می­پذیرد. مزیت عمده الگوریتم پیشنهادی سرعت بالای آن بوده بطوریکه استفاده از آنرا برای کاربردهای بلادرنگ امکان­پذیر می­سازد. Manuscript profile -
Open Access Article
42 - A case study for utilization of image processing in jointed network detection in open-pit mining
Moosa Bagheri Shendi Mehdi Azarafza -
Open Access Article
43 - Application of Image Processing Techniques for Geometrical Simulation in Rock Slopes
Ali Jeddi Zahra Jeddi -
Open Access Article
44 - High-order image processing technique for concrete automatic crack recognition
Hossein Azizi Seadabadi -
Open Access Article
45 - Identify the Components of Artificial Intelligence in Iranian Databases
Mohammad Hassan Azimi samira esmaeiliObjective: The purpose of this study was to identify the components of artificial intelligence in Iranian databases and the rate of its use in these databases.Methodology: This research is an applied and has done by documentary and survey method. The statistical populat MoreObjective: The purpose of this study was to identify the components of artificial intelligence in Iranian databases and the rate of its use in these databases.Methodology: This research is an applied and has done by documentary and survey method. The statistical population of this research includes 7 internal databases (Normags, Norlib, Magiran, Civilica, Irandoc, ISC and SID). Data collection tools were researcher-made notes and checklists and interviews with experts. Data analysis was performed using SPSS software.Results: The results showed that Irandoc database had the most and Civilica and Magiran databases had the least use of artificial intelligence components. It also has the most used components in databases and components. Components of "word Disambiguation in text", "name recognition and classification", "image translators", "description" "Image", "Speech to text conversion", "Text to speech conversion", "Audio translators" have had the least use in databases.Conclusion: The results showed that the use of artificial intelligence components in Iranian databases can accelerate and facilitate the processes of processing, storing and retrieving resources in Iranian databases. Manuscript profile -
Open Access Article
46 - A Review of Notable Studies on Using Empirical Mode Decomposition for Biomedical Signal and Image Processing
Fereshteh Yousefi Rizi -
Open Access Article
47 - Development of a Novel Method for Predicting Root Canals Working Length by Analyzing Dental Radiographs
Ahmad Moghadam Mohammad Adeli -
Open Access Article
48 - Investigation and Simulation of Different Medical Image Processing Algorithms to Improve Image Quality Using Simulink MATLAB
Parissa Salehi Neda Behzadfar -
Open Access Article
49 - Quality classification of tomato plant in field conditions using EfficientNet deep learning model
Mounes Astani Mohammad Hasheminejad Mahsa VaghefiThe appropriateness of the agricultural economy is very effective in sustainable food security. The appearance and shape of agricultural products change in different periods. The correct classification of the product in terms of quality after harvest affects the economy MoreThe appropriateness of the agricultural economy is very effective in sustainable food security. The appearance and shape of agricultural products change in different periods. The correct classification of the product in terms of quality after harvest affects the economy of farmers. Today, deep learning classifiers have greatly contributed to the correct classification of product quality. But the database challenges and the same conditions of the database in the training and testing phase affect the classification accuracy. The purpose of this article is to classify the quality of tomatoes in the challenging conditions of the database, including crowded backgrounds, noise in the image, leaves of the same color as the fruit in the image, and the similarity of growth stages. For this purpose, 3 databases with different challenges have been used in the stage of classification training and testing. In this article, the aim is to classify the quality of tomatoes into 3 classes ripe, unripe ,and semi-ripe using Efficientnet deep learning classifier. According to the conditions of the database, the first three processes of noise removal, image contrast improvement ,and image segmentation have been applied to the images. The results of the evaluation of the proposed method show the proper performance of EfficientnetB5. Manuscript profile -
Open Access Article
50 - Determining Effective Features for Face Detection Using a Hybrid Feature Approach
Sepideh Araban Fardad Farokhi Kaveh Kangarloo -
Open Access Article
51 - Application of Artificial Neural Networks (ANN) and Image Processing for Prediction of Gravimetrical Properties of Roasted Pistachio Nuts and Kernels
Toktam Mohammadi Moghaddam Mohammad Ali Razavi -
Open Access Article
52 - Application of Artificial Neural Networks (ANN) and Image Processing for Prediction of the Geometrical Properties of Roasted Pistachio Nuts and Kernels
Toktam Mohammadi Moghaddamm Seyed Mohammad Ali Razavi -
Open Access Article
53 - Measuring of temperature in steel bar using machine vision system and genetic algorithm in variable conditions
مهدی عباسقلی پور Behzad Mohammadialasti جلال الدین قضاوتیThe temperature measurement of steel bar is a significant parameter in the hot-rolled steel processing. Furthermore, measuring of steel bar temperature at real time requires an automatic intelligent electronic system such as machine vision system. In this study, a machi MoreThe temperature measurement of steel bar is a significant parameter in the hot-rolled steel processing. Furthermore, measuring of steel bar temperature at real time requires an automatic intelligent electronic system such as machine vision system. In this study, a machine vision system is proposed (designed)to provide appropriate images of the steel bar in furnace, process images based on discrimination thresholds and to extract feature (the temperature measurement of steel bar). The threshold limit value for three different temperature ranges; (1200°C -1500°C), (900°C -1200°C) and (600°C -900°C) are assumed to be 1, 2 and 3, respectively, to investigate and analyze variable lighting conditions in HSI color space using genetic algorithm (GA HSI). The performance analysis of proposed GA HSI reveals that color image segmentation by GA HSI and cluster analysis method have the same performance. Therefore, this method can overcome the effect of lighting conditions with acceptance of an error range. Manuscript profile -
Open Access Article
54 - Road detection by image processing, using neural network
Ahmad Keshavarzi Mehdi Keshavarz Alireza Moradi -
Open Access Article
55 - Designing a robot to follow a command from the analysis of the image received from the operator
Majid Amiri Shayan Farokhi Aleh Kouhi Ahmad Keshavarzi