An Efficient Face Recognition under Varying Image Conditions 

Abstract

Performance of the face verification system depends on many conditions. One of the most problematic is varying illumination condition. Making recognition more reliable under uncontrolled lighting conditions is one of the most important challenges for practical face recognition systems. Our paper presents a simple and efficient preprocessing method that eliminates most of the effects of changing illumination and shadows while still preserving the essential appearance details that are needed for recognition. This preprocessing method run before feature extraction that incorporates a series of stages designed to counter the effects of illumination variations, local shadowing, and highlights while preserving the essential elements of visual appearance.In this paper, proposed a robust Face Recognition System under uncontrolled illumination variation. In this Face recognition system consists of three phases, illumination insensitive preprocessing method, Feature-extraction and score fusion. In the preprocessing stage illumination sensitive image transformed into illumination-insensitive image, and then to combines multiple classifiers with complementary features instead of improving the accuracy of a single classifier. Score fusion computes a weighted sum of scores, where the weight is am measure of the discriminating power of the component classifier. In this system demonstrated successful accuracy in face recognition under different illumination condition. The method provides good performance on three sets that are widely used for testing under difficult lighting conditions: Extended Yale-B, Face Recognition Grand Challenge Version 2 experiment (FRGC-204), FERET datasets. The results obtained from the experiments showed that the illumination preprocessing methods significantly improves the recognition rate and it’s a very important step in face verification system. 

Authors and Affiliations

C. Kanimozh , V. Nirmala

Keywords

Related Articles

Study of Wireless Optical CDMA LAN in Indoor Environment 

In this paper we present a deeper view on the methods and the application considered in wireless Optical Code Division Multiple Access (OCDMA) systems. The high cost of reconfiguring and maintaining in wired networ...

Analyzing Knowledge Based Feature Selection to Detect Remote to Local Attacks

Intrusion Detection (ID) is the most significant component in Network Security System as it is responsible to detect several types of attacks. The IDS commonly deals with a large amount of data traffic, which involves ir...

Morphological Processor for Inflectional Case of Multipurpose Lexico-Conceptual Knowledge Resource  

Myanmar language is morphologically rich and agglutinative language. Myanmar words are postpositionally inflected with various grammatical features which can cause difficulties for Language Acquisition (LA). LA is...

HOST SELECTION METHODOLOGY IN CLOUD COMPUTING ENVIRONMENT 

Cloud computing is a paradigm in which IT (information technology) application provide as a service. It allows users to utilize on-demand computation over internet, which is helpful for storage of data and servic...

Model for Intrusion Detection System with Data Mining 

Today internet has become very popular medium to communicate between users publicly, due to this, lots of intruder has spread across the internet that perform malicious activity and attack to destroy useful informa...

Download PDF file
  • EP ID EP136108
  • DOI -
  • Views 90
  • Downloads 0

How To Cite

C. Kanimozh, V. Nirmala (2013). An Efficient Face Recognition under Varying Image Conditions . International Journal of Advanced Research in Computer Engineering & Technology(IJARCET), 2(2), 481-485. https://europub.co.uk/articles/-A-136108