Image Retrieval System with User Relevance Feedback
نویسندگان
چکیده
Image retrieval approach by proposing a new image feature detector and descriptor, namely the micro-structure descriptor (MSD). We present a computational model of creative design based on collaborative interactive genetic algorithms. This Paper test our model on floor planning. This Paper guide the evolution of floorplan based on subjective and objective criteria. The subjective criteria consists of designers picking the floorplan they like the best from a population of floorplans, and the objective criteria consists of coded architectural guidelines. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as Gabor features and multi-textons histogram, for image retrieval.
منابع مشابه
بازیابی 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 کاملDocument 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 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 کاملAdvanced Relevance Feedback Strategy for Precise Image Retrieval
Relevance feedback is effective technique for bridging the semantic gap in image retrieval which diminish semantic gap between low-level visual features and high-level semantic concepts for image retrieval. Currently, crucial image retrieval system is content-based image retrieval. To improve performance of proposed content based image retrieval system, automatic relevance feedback technique is...
متن کاملMatching Scores of System Relevance and User-Oriented Relevance in SID, ISC and Google Scholar
Background and Aim: The main aim of Information storage and retrieval systems is keeping and retrieving the related information means providing the related documents with users’ needs or requests. This study aimed to answer this question that how much are the system relevance and User- Oriented relevance are matched in SID, SCI and Google Scholar databases. Method: In this study 15 keywords of ...
متن کاملInteractive Content-Based Image Retrieval Using Relevance Feedback
Database search engines are generally used in a one-shot fashion in which a user provides query information to the system and, in return, the system provides a number of database instances to the user. A relevance feedback system allows the user to indicate to the system which of these instances are desirable, or relevant, and which are not. Based on this feedback, the system modifies its retri...
متن کامل