face detection

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1 - شناسایی چهره افراد بر اساس مدل معنایی برای موبایل بانک
لیلی نصرتی امیرمسعود بیدگلی حمید حاج سید جوادی

چکیده: در این مقاله، یک پروتکل احراز هویت جدید برای بانکداری آنلاین بر اساس مدل معنایی ویژگی¬های استخراج شده از تصویر افراد معرفی شده است. رویکرد پیشنهادی با استفاده از تلفن¬های همراه هوشمند برای تصویربرداری دیجیتال برای مشتریان ارائه شده است. در این روش از خوشه‌بندی فا چکیده کامل

چکیده: در این مقاله، یک پروتکل احراز هویت جدید برای بانکداری آنلاین بر اساس مدل معنایی ویژگی¬های استخراج شده از تصویر افراد معرفی شده است. رویکرد پیشنهادی با استفاده از تلفن¬های همراه هوشمند برای تصویربرداری دیجیتال برای مشتریان ارائه شده است. در این روش از خوشه‌بندی فازی برای دسته‌بندی ویژگی‌های تصاویر افراد مختلف استفاده شده است و با اعمال آن‌ها در روش‌های مختلف یادگیری ماشین، ترکیب روش‌های طبقه‌بندی یادگیری ماشینی برای بهبود عملکرد و افزایش قدرت در برابر حملات مختلف ارائه شده است. همچنین به منظور کاهش پیچیدگی طراحی ماشین برای کارهای عملیاتی، از روش کاهش ویژگی¬های استخراج شده از تصاویر چهره افراد به کمک الگوریتم ژنتیک و در قسمت آخر برای تصمیم¬گیری جهت احراز هویت فرد انتخاب شده، از سیستم منطق فازی بر اساس بالاترین دقت شناسایی فرد مورد نظر استفاده شده است. با استفاده از یک مجموعه داده عمومی، نتایج تجربی نشان داد که روش مبتنی بر الگوریتم ژنتیک بهترین انتخاب ویژگی برای ایجاد یک روش احراز هویت ضمنی برای محیط تلفن هوشمند است. نتیجه محاسبات دقت حدود 80/99% را با استفاده از تنها 30 ویژگی از 77 ویژگی برای احراز هویت کاربران نشان داد که بیانگر نیاز به منابع کمتر تلفن همراه است. پرونده مقاله

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2 - Human Face Detection in Color Images using Fusion of Ada Boost and LBP Feature
Majid Emadi Mehran Emadi

Face recognition has been one of the most widely used sub-disciplines of machine learning for so many years. Face detection has been employed as an effective method in a wide range of applications such as surveillance systems and Forensic pathology in the area of machin چکیده کامل

Face recognition has been one of the most widely used sub-disciplines of machine learning for so many years. Face detection has been employed as an effective method in a wide range of applications such as surveillance systems and Forensic pathology in the area of machine vision. However, the accuracy of face detection has dramatically declined over the past decade due to wide-ranging challenges such as face detection with changes in face angle, the density of the crowds in an image, quality of light, etc which require special attention of researchers in response to these challenges. In the present study, a new sustainable approach to light changes for face detection based on local features is employed. In this method, the local binary pattern is extracted from face images and Principal Component Analysis is utilized to reduce the feature vectors’ dimension by the descriptor. Eventually, the features are classified using Ada Boost. Tests done on the images on the web show that face recognition accuracy is 100% in the low density crowd, 96% in the high-density crowd and proper light conditions, and 90% in the high-density crowd and poor light conditions. پرونده مقاله

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3 - Providing a hybrid method for face detection, gender recognition, facial landmarks localization and pose estimation using deep learning to improve accuracy
peyman jabraelzadeh Asghar charmin Mohsen Ebadpore

In general, identifying and locating faces in images or videos is considered as the first step in face recognition. It is quite clear that an accurate detection algorithm can significantly benefit system performance and vice versa. Therefore, face recognition is one of چکیده کامل

In general, identifying and locating faces in images or videos is considered as the first step in face recognition. It is quite clear that an accurate detection algorithm can significantly benefit system performance and vice versa. Therefore, face recognition is one of the key steps in the application of face recognition systems. In deep learning algorithms are able to learn high-level features, which have been highly regarded by researchers for use in the field of machine vision, as well as in a variety of fields such as image classification and human gesture estimation, which are the key activities for image perception. In this paper, we present a hybrid method called Hyper-Yolo-face to identify faces, facial landmarks localization, pose estimation and recognize the gender of a given image using deep convolutional neural networks, the Yolo algorithm, and local binary patterns. The proposed network architecture is based on the AlexNet model and the integration of the binary pattern operator and Yolov3, which results in increasing performance and accuracy. Yolo changes the architecture of face recognition systems and looks at the problem of recognition as a regression problem which goes directly from the pixels of the image to the coordinates of the box and the probability of the classes. Experiments on the AFLW and FDDB datasets indicated that the proposed model performs significantly better than other algorithms and methods and improves detection accuracy. پرونده مقاله

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4 - The Combinational Use Of Knowledge-Based Methods and Morphological Image Processing in Color Image Face Detection
Sima Emami1 Emami Ramin Meshkabadi

The human facial recognition is the base for all facial processing systems. In this work a basicmethod is presented for the reduction of detection time in fixed image with different color levels.The proposed method is the simplest approach in face spatial localization, چکیده کامل

The human facial recognition is the base for all facial processing systems. In this work a basicmethod is presented for the reduction of detection time in fixed image with different color levels.The proposed method is the simplest approach in face spatial localization, since it doesn’trequire the dynamics of images and information of the color of skin in image background. Inaddition, to do face recognition, there is no need for the existence of image. For the extraction offacial features, the combination of knowledge-based and morphological image processingmethods is utilized, which has a high accuracy, compared to other methods. The proposedmethod is analyzed by MATLAB software and tested on different images which demonstratedhigh accuracy and efficiency of the method. پرونده مقاله

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5 - Face Detection with methods based on color by using Artificial Neural Network
Reza Abbasgolizadeh Habib Izadkhah Ramin Meshkabadi

The face Detection methodsis used in order to provide security. The mentioned methods problems are that it cannot be categorized because of the great differences and varieties in the face of individuals. In this paper, face Detection methods has been presented for overc چکیده کامل

The face Detection methodsis used in order to provide security. The mentioned methods problems are that it cannot be categorized because of the great differences and varieties in the face of individuals. In this paper, face Detection methods has been presented for overcoming upon these problems based on skin color datum. The researcher gathered a face database of 30 individuals consisting of over 450 facial images to test fully automated face detection without verification, fully automated face detection with verification, manual face detection and automated face recognition, fully automated face detection and recognition and pose invariant face recognition. Successful results were obtained for automated face detection and for automated face recognition under robust conditions. In presented method, Scratch using Gaussian filter and morphology processing of the face areawould be selected and more complex neural network has been trained with over 200 images and totally, Three different sets of various images have been studied in terms of appearance number and lighting and quality. The experimental results showed the reliability of this method. In fact, by offering face recognition algorithm with color by artificial neural network is able to identify different types of faces. The accurateness of the proposed method would be more than 95 percent. پرونده مقاله

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6 - The Mechanical Design of Drowsiness Detection Using Color Based Features
Peyman jabraelzade Rahim parikhani

This paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. This system can be used in multiple places. For example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver چکیده کامل

This paper demonstrates design and fabrication o f a mechatronic system for human drowsiness detection. This system can be used in multiple places. For example, in factories, it is used on some dangerous machinery and in cars in order t o prevent the operator o r driver from falling asleep. This system is composed of three parts: (1) mechanical, (2) electrical and (3) image processing system. After processing the input image and eye position detection, the system investigates the state of the eye, and in the case of drowsiness, the system activates the alarm. It also has the ability to tra ck the eyes. پرونده مقاله

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