The aim of this paper is to detect abnormal events in video streams, a challenging but important subject in video surveillance. A novel algorithm is proposed to address this problem. The algorithm is based on an image descriptor and a nonlinear classification method. The images are subjected to Otsu’s method for global thresholding. A histogram of optical flow orientation as a descriptor encodi...

Abstract As a generalization of the fuzzy soft set, interval-valued set is viewed as more resilient and powerful tool for dealing with uncertain information. However, lower or upper membership degree, both them, may be missed during data collection transmission procedure, which could present challenges processing. The existing filling algorithm incomplete sets has low accuracy high error rate l...

Data Science is a fairly novel field, and it predominantly deals with analysis assortment of data. Machine Learning field that goes hand in this regard. Various Algorithms, which are trained on dataset predict results based their training, thus the accuracy model determined by testing dataset. Foreground feature extraction another interesting application. Using data visualization processing, we...

In this paper we propose a novel method for face recognition using hybrid SPCA-KNN (SIFT-PCAKNN) approach. The proposed method consists of three parts. The first part is based on preprocessing face images using Graph Based algorithm and SIFT (Scale Invariant Feature Transform) descriptor. Graph Based topology is used for matching two face images. In the second part eigen values and eigen vector...

Echoed parts of Quranic accent (Qiraat) signals are exposed to reverberation of signals especially if they are listened to in a conference room or the Quranic recordings found in different media such as the web. Quranic verse rules identification/Tajweed are prone to additive noise and may reduce classification results. This research work aims to present our work towards Quranic accents (Qiraat...