European Conference on Computer Vision (ECCV) 1996 In its traditional formulation, stereo correspondence involves both searching and selecting. Given a feature in one scanline, the corresponding scanline in the other image is searched for the positions of similar features. Often more than one candidate is found, and the correct one must be selected. The problem of selection is unavoidable becau...

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The ...

Robust image hashing methods require the robustness to content preserving processing and geometric transform. Zernike moment is a local image feature descriptor whose magnitude components are rotationally invariant and most suitable for image hashing application. In this paper, we proposed Geometric invariant robust image hashing via zernike momment. Normalized zernike moments of an image are u...

Among the chief applications of the MPEG-7 visual descriptors is image indexing and retrieval. And among the colour image descriptors in the Standard having the best retrieval performance is the Colour Structure (CS) Descriptor, a descriptor that uses no more storage than an ordinary colour histogram but that substantially out-performs it. The basis of the CS Descriptor is the CS histogram, a g...

Approaches for the detection of points of interest (POI) have been applied to several different problems in computer vision, like motion tracking, image registration, object recognition, video indexing, and even texture classification. Since accompanied by corresponding local image descriptors, they have received growing attention. Current approaches completely remain in the two dimensions of t...

A novel descriptor able to improve the classification capabilities of a typical pattern recognition system is proposed in this paper. The introduced descriptor is derived by incorporating two efficient region descriptors, namely image moments and Local Binary Patterns (LBP), commonly used in pattern recognition applications, in the last decades. The main idea behind this novel feature extractio...

This paper proposes an augmented version of local feature that enhances the discriminative power of the feature without affecting its invariance to image deformations. The idea is about learning local features, aiming to estimate its semantic, which is then exploited in conjunction with the bag of words paradigm to build an augmented feature descriptor. Basically, any local descriptor can be ca...