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Shape context is a classic shape retrieval method with translation invariance, but it has not scalar or rotational invariance, which limits its application. A new shape feature descriptor-centroid distance ratio (CdR) is proposed and an improved shape retrieval algorithm based on CdR and shape context is brought forth. First, the contour points are sampled in order to reduce computation and then,...
In this paper, we propose a noise removal approach that significantly improves the performance of sophisticated shape matching techniques. Existing shape matching techniques focus on complex algorithms without giving much consideration to the noise removing preprocessing techniques. These preprocessing techniques can reasonably improve the accuracy where the shapes are affected by cracks. We present...
The paper proposed a new image matching method combining affine-invariant SIFT feature descriptor with global context. Affine-SIFT (ASIFT) can find large numbers of correct matches even with great variation of camera axis orientation, however when there are several similar regions or objects between the query and search images, it may also produce many mismatches. Therefore, we intend to introduce...
This paper demonstrates, to our best knowledge, the first attempt on gender and ethnicity identification from silhouetted face profiles using a computer vision technique. The results achieved, after testing on 441 images, show that silhouetted face profiles have a lot of information, in particular, for ethnicity identification. Shape context based matching was employed for classification. The test...
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