An Efficient Method for Face Recognition System In Various Assorted Conditions

In the beginning stage, face verification is done using easy method of geometric algorithm models, but the verification route has now developed into a scientific progress of complicated geometric representation and identical procedure. In recent years the technologies have boosted face recognition system into the healthy focus. Researchers currently undergoing strong research on finding face recognition system for wider area information taken under hysterical elucidation dissimilarity. The proposed face recognition system consists of a narrative expositionindiscreet preprocessing method, a hybrid Fourier-based facial feature extraction and a score fusion scheme. We have verified the face recognition in different lightening conditions (day or night) and at different locations (indoor or outdoor). Preprocessing, Image detection, Feature- extraction and Face recognition are the methods used for face verification system. This paper focuses mainly on the issue of toughness to lighting variations. The proposed system has obtained an average of 88.1% verification rate on Two-Dimensional images under different lightening conditions.

Localization of License Plate Using Morphological Operations

It is believed that there are currently millions of vehicles on the roads worldwide. The over speed of vehicles,theft of vehicles, disobeying traffic rules in public, an unauthorized person entering the restricted area are keep on increasing. In order restrict against these criminal activities, we need an automatic public security system. Each vehicle has their own Vehicle Identification Number (VIN) as their primary identifier. The VIN is actually a License Number which states a legal license to participate in the public traffic. The proposed paper is to identify the vehicle with the help of vehicles License Plate (LP).LPRS is one the most important part of the Intelligent Transportation System (ITS) to locate the LP. In this paper certain existing algorithm drawbacks are overcome by the proposed morphological operations for LPRS. Morphological operation is chosen due to its higher efficiency, noise filter capacity, accuracy, exact localization of LP and speed.

A Novel Histogram Based Robust Image Registration Technique

In this paper, a method for Automatic Image Registration (AIR) through histogram is proposed. Automatic image registration is one of the crucial steps in the analysis of remotely sensed data. A new acquired image must be transformed, using image registration techniques, to match the orientation and scale of previous related images. This new approach combines several segmentations of the pair of images to be registered. A relaxation parameter on the histogram modes delineation is introduced. It is followed by characterization of the extracted objects through the objects area, axis ratio, and perimeter and fractal dimension. The matched objects are used for rotation and translation estimation. It allows for the registration of pairs of images with differences in rotation and translation. This method contributes to subpixel accuracy.

A Narrative Vehicle Protection Representation for Vehicle Speed Regulator Under Driver Exhaustion -- A Study

Driver fatigue is one of the important factors that cause traffic accidents, and the ever-increasing number due to diminished drivers vigilance level has become a problem of serious concern to society. Drivers with a diminished vigilance level suffer from a marked decline in their abilities of perception, recognition, and vehicle control, and therefore pose serious danger to their own life and the lives of other people. Exhaustion resulting from sleep deprivation or sleep disorders is an important factor in the creasing number of accidents. In this projected work, we discuss the various methods of the existing and the proposed method based on a real time online safety prototype that controls the vehicle speed under driver fatigue. The purpose of such a model is to advance a system to detect fatigue symptoms in drivers and control the speed of vehicle to avoid accidents. This system was tested adequately with subjects of different technology of various researchers finally the validity of the proposed model for vehicle speed controller based on driver fatigue detection is shown.

Ontology - Based Dynamic Business Process Customization

The interaction between business models is used in consumer centric manner instead of using a producer centric approach for customizing the business process in cloud environment. The knowledge based human semantic web is used for customizing the business process It introduces the Human Semantic Web as a conceptual interface, providing human-understandable semantics on top of the ordinary Semantic Web, which provides machine-readable semantics based on RDF in this mismatching is a major problem. To overcome this following technique automatic customization detection is an automated process of detecting possible elements or variables of a business process that needto be especially treated in order to suit the requirement of the other process. To the business processto be customized as the primary business process and those that it collaborates with as secondary business process or SBP Automatic customization enactment is an automated process of taking actions to perform the customization on the PBP according to the detected customization spots and the automatic reasoning on the customization conceptualization knowledge framework. The process of customizing businessprocesses by composite the web pages by using web service.

Face Verification Using Kernel Principle Component Analysis

In the beginning stage, face verification is done using easy method of geometric algorithm models, but the verification route has now developed into a scientific progress of complicated geometric representation and matching process. In modern time the skill have enhanced face detection system into the vigorous focal point. Researchers currently undergoing strong research on finding face recognition system for wider area information taken under hysterical elucidation dissimilarity. The proposed face recognition system consists of a narrative exposition indiscreet preprocessing method, a hybrid Fourier-based facial feature extraction and a score fusion scheme. We take in conventional the face detection in unlike cheer up circumstances and at unusual setting. Image processing, Image detection, Feature removal and Face detection are the methods used for Face Verification System . This paper focuses mainly on the issue of toughness to lighting variations. The proposed system has obtained an average of verification rate on Two-Dimensional images under different lightening conditions.

Face Verification System based on Integral Normalized Gradient Image(INGI)

Character identification plays a vital role in the contemporary world of Image processing. It can solve many composite problems and makes humans work easier. An instance is Handwritten Character detection. Handwritten recognition is not a novel expertise, but it has not gained community notice until Now. The eventual aim of designing Handwritten Character recognition structure with an accurateness rate of 100% is pretty illusionary. Tamil Handwritten Character recognition system uses the Neural Networks to distinguish them. Neural Network and structural characteristics are used to instruct and recognize written characters. After training and testing the exactness rate reached 99%. This correctness rate is extremely high. In this paper we are exploring image processing through the Hilditch algorithm foundation and structural characteristics of a character in the image. And we recognized some character of the Tamil language, and we are trying to identify all the character of Tamil In our future works.

Hilditchs Algorithm Based Tamil Character Recognition

Character identification plays a vital role in the contemporary world of Image processing. It can solve many composite problems and makes humans work easier. An instance is Handwritten Character detection. Handwritten recognition is not a novel expertise, but it has not gained community notice until Now. The eventual aim of designing Handwritten Character recognition structure with an accurateness rate of 100% is pretty illusionary. Tamil Handwritten Character recognition system uses the Neural Networks to distinguish them. Neural Network and structural characteristics are used to instruct and recognize written characters. After training and testing the exactness rate reached 99%. This correctness rate is extremely high. In this paper we are exploring image processing through the Hilditch algorithm foundation and structural characteristics of a character in the image. And we recognized some character of the Tamil language, and we are trying to identify all the character of Tamil In our future works.

An Efficient Method for Recognizing the Low Quality Fingerprint Verification by Means of Cross Correlation

In this paper, we propose an efficient method to provide personal identification using fingerprint to get better accuracy even in noisy condition. The fingerprint matching based on the number of corresponding minutia pairings, has been in use for a long time, which is not very efficient for recognizing the low quality fingerprints. To overcome this problem, correlation technique is used. The correlation-based fingerprint verification system is capable of dealing with low quality images from which no minutiae can be extracted reliably and with fingerprints that suffer from non-uniform shape distortions, also in case of damaged and partial images. Orientation Field Methodology (OFM) has been used as a preprocessing module, and it converts the images into a field pattern based on the direction of the ridges, loops and bifurcations in the image of a fingerprint. The input image is then Cross Correlated (CC) with all the images in the cluster and the highest correlated image is taken as the output. The result gives a good recognition rate, as the proposed scheme uses Cross Correlation of Field Orientation (CCFO = OFM + CC) for fingerprint identification.

A New Approach to the Solution of Economic Dispatch Using Particle Swarm Optimization with Simulated Annealing

A new approach to the solution of Economic Dispatch using Particle Swarm Optimization is presented. It is the progression of allocating production amongst the dedicated units such that the restriction forced are fulfilled and the power needs are reduced. More just, the soft computing method has received supplementary concentration and was used in a quantity of successful and sensible applications. Here, an attempt has been made to find out the minimum cost by using Particle Swarm Optimization Algorithm using the data of three generating units. In this work, data has been taken such as the loss coefficients with the max-min power limit and cost function. PSO and Simulated Annealing are functional to put out the least amount for dissimilar energy requirements. When the outputs are compared with the conventional method, PSO seems to give an improved result with enhanced convergence feature. All the methods are executed in MATLAB environment. The effectiveness and feasibility of the proposed method were demonstrated by three generating units case study. Output gives hopeful results, signifying that the projected method of calculation is competent of economically formative advanced eminence solutions addressing economic dispatch problems.