Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user
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Content-based image retrieval and text-based image retrieval are two fundamental approaches in the field of image retrieval. The challenges related to each of these approaches, guide the researchers to use combining approaches and semi-automatic retrieval using the user interaction in the retrieval cycle. Hence, in this paper, an image retrieval system is introduced that provided two kind of query presenting, query by keyword and query by sample image. The proposed system, after the first result retrieval, does an interactive retrieval process semantically based on user's relevance feedbacks and related high level semantic labels to the images semi-automatically. This system can reply different requests in the image retrieval domain based on a hierarchical semantic network and doing a kind of learning process by the feedbacks given by user. According to experiments, the proposed approach concludes acceptable accuracy for retrieval results
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