Face Recognition using Feature Extraction and Fuzzy Classification

Abstract

Automatic face recognition is a significant problem that has many real life applications. Not only highly secured places in military bases, but also different civilian office applications require automatic face recognition systems. The face recognition system introduced in this paper extracts a set of features from a captured picture of a face, represents these features as ratios in a feature vector, and presents the generated feature vector to a classifier system to recognize the face. The features are approximately located by histograms and refined by elastic template matching. Six distance measures are applied in a nearest-neighbor classification model. Two standard distance measures and four fuzzy distance measures are implemented. For the best measure, recognition success was 90% in the best case and 87.5% in the average case.

Department(s)

Engineering Management and Systems Engineering

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 The Authors, All rights reserved.

Publication Date

01 Dec 1995

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