In this paper, we proposed a rotation invariant image descriptor based on Radon transform (RT) and energy operator. Radon transform captures the directional features of the pattern image by projecting the pattern onto different orientation slices, and its most attractive ability is to transform rotational components to circular shift components. Meanwhile, the energy operator can remove the cir...

Based on log-polar mapping and phase correlation, this paper presents a novel digital image watermarking scheme that is invariant to rotation, scaling, and translation (RST). We embed watermark in the log-polar mappings of Fourier magnitude spectrum of original image, and use the phase correlation between the LPM of the original image and the LPM of the watermarked image to calculate the displa...

I. Biederman and P. C. Gerhardstein (1993) demonstrated that a representation specifying a distinctive arrangement of viewpoint-invariant parts (a geon structural description, [GSD]) dramatically reduced the costs of rotation in depth. M. J. Tarr and H. H. Bulthoff (1995) attempt to make a case for viewpoint-dependent mechanisms, such as mental rotation. Their suggestion that GSDs enjoy no spec...

This paper proposes an approach to compute an EOH (edge-oriented histogram) descriptor with main orientation. EOH has a better matching ability than SIFT (scale-invariant feature transform) on multispectral images, but does not assign a main orientation to keypoints. Alternatively, it tends to assign the same main orientation to every keypoint, e.g., zero degrees. This limits EOH to matching ke...

Watermark refers to digital data embedded in cover data with an intent of copyright protection or proof of ownership. In case of image watermarking, the robustness of watermarks to geometric attacks is considered to be the most challenging design requirements for watermarks. Geometric attacks like Rotation, Scaling and Translation (RST attacks) can desynchronize the location of the watermark an...

Gaussian curvature is an invariant local descriptor of smooth surfaces. We present an object signature which is a condensed representation of the distribution of Gaussian curvature information at visible object points. An invariant related to Gaussian curvature at a point is derived from the covariance matrix of the photometric values in a neighborhood about that point. In addition, we introduc...

Aggregation of local features is a well-studied approach for image as well as 3D model retrieval (3DMR). A carefully designed local 3D geometric feature is able to describe detailed local geometry of 3D model, often with invariance to geometric transformations that include 3D rotation of local 3D regions. For efficient 3DMR, these local features are aggregated into a feature per 3D model. A rec...

Conventional regular moment functions have been proposed as pattern sensitive features in image classi®cation and recognition applications. But conventional regular moments are only invariant to translation, rotation and equal scaling. It is shown that the conventional regular moment invariants remain no longer invariant when the image is scaled unequally in the xand y-axis directions. We addre...