Relevance Feedback for Content-Based Image Retrieval Using Bayesian Network
نویسندگان
چکیده
Relevance feedback is a powerful query modification technique in the field of content-based image retrieval. The key issue in relevance feedback is how to effectively utilize the feedback information to improve the retrieval performance. This paper presents a relevance feedback scheme using Bayesian network model for feedback information adoption. Relevant images during previous iterations are reasonably incorporated into the current iteration and the chosen relevant images can better capture user’s information need.
منابع مشابه
Document Image Retrieval Based on Keyword Spotting Using Relevance Feedback
Keyword Spotting is a well-known method in document image retrieval. In this method, Search in document images is based on query word image. In this Paper, an approach for document image retrieval based on keyword spotting has been proposed. In proposed method, a framework using relevance feedback is presented. Relevance feedback, an interactive and efficient method is used in this paper to imp...
متن کاملRelevance feedback using a Bayesian classifier in content-based image retrieval
As an effective solution of the content-based image retrieval (CBIR) problems, relevance feedback has been put on many efforts for the past few years. In this paper, we propose a new relevance feedback approach with progressive leaning capability. It is based on a Bayesian classifier and treats positive and negative feedback examples with different strategies. It can utilize previous users’ fee...
متن کاملبازیابی تعاملی تصاویر طبیعت با بهره گیری از یادگیری چند نمونه ای
Content-based image retrieval (CBIR) has received considerable research interest in the recent years. The basic problem in CBIR is the semantic gap between the high-level image semantics and the low-level image features. Region-based image retrieval and learning from user interaction through relevance feedback are two main approaches to solving this problem. Recently, the research in integra...
متن کاملSemiautomatic Image Retrieval Using the High Level Semantic Labels
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 qu...
متن کاملUsing Bayesian classifier in relevant feedback of image retrieval
Relevance feedback is a powerful technique in contentbased image retrieval (CBIR) and has been an active research area for the past few years. In this paper, we propose a new relevance feedback approach based on Bayesian classifier and it treats positive and negative feedback examples with different strategies. For positive examples, a Bayesian classifier is used to determine the distribution o...
متن کامل