Using biometric technology for recording attendance in the school environment is still not widely done by researchers. In this study, a solution was proposed to problems that occurred where parents/guardians could monitor presence of their children school. The offered student system based on facial recognition algorithms (face recognition). built can record students when entering classroom and ...

Rapid social development has resulted in the emergence of a new major societal issue: urban traffic congestion, which many cities must address. In addition to making it more difficult for people get around town, jams are source city's pollution crisis. order address problems automobile exhaust and this paper uses system dynamics approach develop model study congestion from perspectives trucks,p...

This informal set of notes contains some of the new results which will appear in the author’s 2013 dissertation. We show that every infinite product of locally compact non-compact groups decomposes into the disjoint union of a Haar null set and a meager set, which gives a partial positive answer to a question of Darji. We also show that the compact sets in each such product group are always Haa...

Face detection is one of the hottest research topics of the field of pattern recognition, image processing, machine vision, and etc. This paper proposes a novel method for fast and reliable face detection, especially in complex background. Firstly, the Haar features of the training image are extracted, and then the training image is divided into small blocks to extract local binary pattern (LBP...

This paper addresses the problem of detecting human faces in noisy images. We propose a method that includes a denoising preprocessing step, and a new face detection approach based on a novel extension of Haar-like features. Preprocessing of the input images is focused on the removal of different types of noise while preserving the phase data. For the face detection process, we introduce the co...

Object detection using Haar-like features is formulated as a maximum likelihood estimation. Object features are described by an arbitrary Bayesian Network (BN) of Haar-like features. We proposed variable translation techniques transform the BN into the likelihood for the object detection. The likelihood is a BN which includes a node that represents the object’s position, angle and scale. The ob...

It is well known that the Haar and Shannon wavelets in L2(R) are at opposite extremes, in the sense that the Haar wavelet is localized in time but not in frequency, whereas the Shannon wavelet is localized in freqency but not in time. We present a rich setting where the Haar and Shannon wavelets coincide and are localized both in time and in frequency. More generally, if R is replaced by a grou...