Parallel Processing for Multi Face Detection and Recognition

In this paper, a robust approach for real time face recognition where the images come from live video is proposed. To improve the algorithmic efficiency of face detection, we combine the eigenface method using Haar-like features to detect both of eyes and face, and Robert cross edge detector to locate the human face position. Robert Cross uses the integral image representation and simple rectangular features to eliminate the need of expensive calculation of multi-scale image pyramid. Moreover, In order to provide fast response in our system, we use Principal Component Analysis (PCA) to reduce the dimensionality of the training set, leaving only those features that are critical for face recognition. Eigendistance is used in face recognition to match the new face while it is projected on the face space. The matching is done when the variation difference between the new image and the stored image is below the threshold value. The experimental results demonstrate that the proposed scheme significantly improves the recognition performance. Overall, we find the system outperforms other techniques. Moreover, the proposed system can be used in different vision-based human computer interaction such as ATM, cell phone, intelligent buildings, etc

Optimized Algorithm for Face Detection Integrating Different Illuminating Conditions

Face detection is a significant research topic to contrive identity for many automated systems. We present a novel face detection algorithm to detect a single face in an image sequence in the real-time environment by finding structural features. The proposed method allows the user to detect the face in case the lighting conditions, pose, and viewpoint vary. The proposed algorithm combines two segmentation approaches. The first approach is a Pixel-based approach by using the components Y, Cb, and Cr in YCbCr color model as threshold conditions to segment the image into luminance and chrominance components. Based on the components of YCbCr color model, the pixel can be classified to have skin tone if it's value is between two specific thresholds. The second approach is an Edgebased approach by using Roberts cross operator. It approximates the magnitude of the gradient of the test image. It also separates the integrated regions into the face and highlights these regions of high spatial gradients which correspond to the edges of the face. The new algorithm achieves high detection rate and low false positive rate

Optimized Algorithm for Fire Detection over WSN using Micaz Motes

Environment degradation around the world has motivated many researchers to deal with an important yet endangering aspect of rural and forest fires. Most of the current developed technologies are based on detection of the fire rather than verifying it. Detecting the fire can be useful in many cases but it is still not efficiently implemented in real time systems. However, detecting fire systems can help many modern cities improve their smoke detection systems. Therefore, in this paper we introduce and implement a fire detecting algorithm built on measuring the temperature of a certain area and detecting the fire. We have also used a mathematical model called the “Acoustic ranging Technique” to detect the location and set the alarm in case of a fire. In our implementation we have used multiple MTS 300 sensor boards mounted on MICAz motes, in order to sense the temperature of the fire with respect to the energy consumption. Hence, with use of the implemented algorithm, we can verify the size of the fire from temperature recorded and analyzed based on the color temperature. Finally, in this paper we could prove that the relation between the type of fire and its colors can be used in detecting the size of the fire efficiently

Efficient and Robust Optical Character Recognition Algorithm for Signature Recognition

With the technology development over the past decades, it became necessary to provide secure recognition systems. The Optical Character Recognition (OCR) can be considered as one of the most useful software to offer security. It works on the principal of recognizing the patterns with the use of a computer algorithm. OCR has multiple uses in places that need security verification such as banks, elevators, police departments. Furthermore, it can be used in several categories simultaneously. There are two types of recognition. First is the static approach which is based on the information of the input. Second is the dynamic recognition which is more usable for recognition of speech. In fact, OCR will be one of the most important techniques for human computer interaction in future. However, in this paper we have used OCR as feature to implement our algorithm. We are presenting a new algorithm that is capable of recognizing each signature individually. This makes the system more efficient and robust,especially in banks which need to verify the customer’s signature on a regular basis. A highly efficient C# system was developed to implement the new algorithm

A New Programming Model to Simulate Wireless Sensor Networks : Finding The Best Routing Path

Sensor networks provide a number of extensive programming challenges for Wireless Sensor Networks (WSNs) application programmers. Application developers have proposed various WSNs programming models to avoid these challenges and make WSN programming much easier. In this work we proposed a new programming model to find the best routing path in WSNs. Then we describe the initial design and the implementation of our proposed model and compare the results in different network topologies and evaluate the new model in terms of cost and accuracy

Development of OSA Event Detection Using Threshold Based Automatic Classification

Obstructive Sleep Apnea (OSA) is a very serious sleeping disorder resulting in the temporary blockage of the airflow airway that can be deadly if left untreated. OSA is not a rare condition; in the US, from 18 to 50 million people, most of them remain undiagnosed due to cost, cumbersome and resource limitations of overnight polysomnography (PSG) at sleep labs. Instead, automated, at-home devices that patients can simply use while asleep seem to be very attractive and highly on-demand. This paper presents a method for OSA screening and user notification based on the respiratory recording and video monitoring as a secondary system during sleep in order to alert of the apnea event and help patient to recover

Topology Management in Wireless Sensor Networks: Multi-State Algorithms

In order to maximize the network’s lifetime and ensure the connectivity among the nodes, most topology management practices use a subgroup of nodes for routing. This paper provides an in-depth look at existing topology management control algorithms in Multi-state structure. We suggest a new algorithm based on Geographical Adaptive Fidelity (GAF) and Adaptive Self-Configuring Sensor Networks Topology (ASCENT). The new proposed algorithm outperforms both GAF and ASCENT algorithms

Reconstructing the demographic history of the Himalayan and adjoining populations

The rugged topography of the Himalayan region has hindered large-scale human migrations, population admixture and assimilation. Such complexity in geographical structure might have facilitated the existence of several small isolated communities in this region. We have genotyped about 850,000 autosomal markers among 35 individuals belonging to the four major populations inhabiting the Himalaya and adjoining regions. In addition, we have genotyped 794 individuals belonging to 16 ethnic groups from the same region, for uniparental (mitochondrial and Y chromosomal DNA) markers. Our results in the light of various statistical analyses suggest a closer link of the Himalayan and adjoining populations to East Asia than their immediate geographical neighbours in South Asia. Allele frequency-based analyses likely support the existence of a specific ancestry component in the Himalayan and adjoining populations. The admixture time estimate suggests a recent westward migration of populations living to the East of the Himalaya. Furthermore, the uniparental marker analysis among the Himalayan and adjoining populations reveal the presence of East, Southeast and South Asian genetic signatures. Interestingly, we observed an antagonistic association of Y chromosomal haplogroups O3 and D clines with the longitudinal distance. Thus, we summarise that studying the Himalayan and adjoining populations is essential for a comprehensive reconstruction of the human evolutionary and ethnolinguistic history of eastern Eurasia