most of the contour detection methods suffers from some drawbacks such as noise, occlusion of objects, shifting, scaling and rotation of objects in image which they suppress the recognition accuracy. to solve the problem, this paper utilizes zernike moment (zm) and pseudo zernike moment (pzm) to extract object contour features in all situations such as rotation, scaling and shifting of object i...

Privacy and interpretability are two important ingredients for achieving trustworthy machine learning. We study the interplay of these aspects in graph learning through reconstruction attacks. The goal adversary here is to reconstruct structure training data given access model explanations. Based on different kinds auxiliary information available adversary, we propose several show that addition...

We present a novel approach for extraction of minutiae features from fingerprint images. The proposed approach is based on the use of logical templates for minutiae extraction in the presence of data distortion. A logical template is an expression that is applied to the binary ridge (valley) image at selected potential locations to detect the presence of minutia at these locations. It is adapte...

Feature extraction and feature selection are two important tasks in pattern recognition. Classiication algorithms like k-nearest neighbors, which are based on the assumption that patterns in the same class are close to each other and those in diierent classes are far apart (locality property), rely heavily on the quality of the features extracted from the input data. In this work, an objective ...