Article ID Journal Published Year Pages File Type
534016 Pattern Recognition Letters 2013 10 Pages PDF
Abstract

•The elliptical neighborhood region is normalized to enhance the invariance to viewpoint change.•The affine scale-space is applied to increase the scale invariance.•The polar histogram orientation bin is used to improve SIFT descriptor’s rotation invariance.•Rearranging the descriptor is used to increase the mirror reflection invariance.

Constructing proper descriptors for interest points in images is a critical aspect for local features related tasks in computer vision and pattern recognition. Although the SIFT descriptor has been proven to perform better than the other existing local descriptors, it does not gain sufficient distinctiveness and robustness in image match especially in the case of affine and mirror transformations, in which many mismatches could occur. This paper presents an improvement to the SIFT descriptor for image matching and retrieval. The framework of the proposed descriptor consists of the following steps: normalizing elliptical neighboring region, transforming to affine scale-space, improving the SIFT descriptor with polar histogram orientation bin, as well as integrating the mirror reflection invariant. A comparative evaluation of different descriptors is carried out showing that the present approach provides better results than the existing methods.

Related Topics
Physical Sciences and Engineering Computer Science Computer Vision and Pattern Recognition
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