Deformation tolerant generalized Hough transform for sketch-based image retrieval in complex scenes

被引:7
作者
Anelli, M.
Cinque, L.
Sangineto, Enver
机构
[1] Elettr SPA, Rome, Italy
[2] Univ Roma La Sapienza, Dipartimento Informat, I-00198 Rome, Italy
关键词
content-based image retrieval; generalized hough transform; unsegmented images; query by sketch; object recognition;
D O I
10.1016/j.imavis.2007.03.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Sketch-based image retrieval systems need to handle two main problems. First of all, they have to recognize shapes similar but not necessarily identical to the user's query. Hence, exact object identification techniques do not fit in this case. The second problem is the selection of the image features to compare with the user's sketch. In domain-independent visual repositories, real-life images with non-uniform background and possible occluding objects make this second task particularly hard. We address the second problem proposing a variant of the well-known Generalized Hough Transform (GHT), which is a robust object identification technique for unsegmented images. Moreover, we solve the first problem modifying the GHT to deal with an inexact matching problem. In this paper, we show how this idea can be efficiently and accurately realized. Experimental results are shown with two different databases of real, unsegmented images. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:1802 / 1813
页数:12
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