Face Recognition using Segmental Euclidean Distance
作者： Farrukh Sayeed , Madasu Hanmandlu , Abdul Quaiyum Ansari
DOI: 10.14429/DSJ.61.1178
关键词:
摘要: In this paper an attempt has been made to detect the face using combination of integral image along with cascade structured classifier which is built Adaboost learning algorithm. The detected faces are then passed through a filtering process for discarding non regions. They individually split up into five segments consisting forehead, eyes, nose, mouth and chin. Each segment considered as separate Eigenface also called principal component analysis (PCA) features each computed. having slight pose aligned proper segmentation. test segmented similarly its PCA found. segmental Euclidean distance used matching stored one. success rate comes out be 88 per cent on CG(full) database created from databases California Institute Georgia Institute. However performance approach ORL(full) same only 70 cent. For sake comparison, DCT(full) fuzzy tried CG ORL but well known classifier, support vector machine (SVM). Results recognition DCT SVM increased by 3 over those due database. results improved 96 SVM. Defence Science Journal, 2011, 61(5), pp.431-442 , DOI:http://dx.doi.org/10.14429/dsj.61.1178
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