Covariate Conscious Approach for Gait Recognition Based Upon Zernike Moment Invariants

Covariate conscious approach for Gait recognition based upon Zernike moment invariants

— Gait recognition i.e. identification of an individual from his/her walking pattern is an emerging field. While existing gait recognition techniques perform satisfactorily in normal walking conditions, there performance tend to suffer drastically with variations in clothing and carrying conditions. In this work, we propose a novel covariate cognizant framework to deal with the presence of such...

A Novel Image Retrieval Approach for Digital Images Based On Pseudo-Zernike Moment Invariants

In this paper we propose a new and effective image retrieval scheme using color, texture and shape features based on pseudo-Zernike moment. Image is predefined by using fast color quantization algorithm with cluster merging. A small number of dominant colors and their percentage can be obtained. The spatial features are extracted using steerable filter decomposition. This offers an efficient an...

Moment Invariants for Object Recognition

Generalized affine moment invariants for object recognition

This paper introduces a new way of extracting affine invariant features from image functions. The presented approach is based on combining affine moment invariants (AMI) with multiscale invariants, in particular multiscale autoconvolution (MSA) and spatial multiscale affine invariants (SMA). Our approach includes all of these invariants as special cases, but also makes it possible to construct ...

Pseudo Zernike Moment-based Multi-frame Super Resolution

The goal of multi-frame Super Resolution (SR) is to fuse multiple Low Resolution (LR) images to produce one High Resolution (HR) image. The major challenge of classic SR approaches is accurate motion estimation between the frames. To handle this challenge, fuzzy motion estimation method has been proposed that replaces value of each pixel using the weighted averaging all its neighboring pixels i...