期刊名称：International Journal of Advanced Research in Computer Engineering & Technology (IJARCET)
印刷版ISSN：2278-1323
出版年度：2017
卷号：6
期号：3
页码：361-365
出版社：Shri Pannalal Research Institute of Technolgy
摘要：A sketch based image retrieval often needs to optimize the trade off between efficiency and precision. Index structures are typically applied to large-scale databases to realize efficient retrievals. However, the quantization errors will affect the performance. Moreover, the uncertainty of user provided examples may also reduce the performance, when compared with traditional image retrieval methods. Sketch based image retrieval systems that preserve the index structure are challenging. In this paper, we propose an effective sketch based image retrieval approach with re-ranking and relevance feedback schemes. Our approach makes full use of the explanation in query sketches and the top ranked images of the initial results. Relevance feedback is applied to find more relevant images for the input query sketch. The integration of the two schemes results in mutual benefits and improves the performance of the sketch based image retrieval.
关键词：Sketch;Sketch Based Image Retrieval (SBIR); Relevance Feedback; Image Retrieval; Contour Matching;Reranking via Visual Feature Verification(RVFV);Contour Based Relevance Feedback(CBRF).
