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http://dx.doi.org/10.9708/jksci.2011.16.1.071

Selection of Optimal Face Detection Algorithms by Fuzzy Inference  

Jang, Dae-Sik (Dept. of Computer Information Engineering, Kunsan National University)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.1, 2011 , pp. 71-80 More about this Journal
Abstract
This paper provides a novel approach for developers to use face detection techniques for their applications easily without special knowledge by selecting optimal face detection algorithms based on fuzzy inference. The purpose of this paper is to come up with a high-level system for face detection based on fuzzy inference with which users can develop systems easily and even without specific knowledge on face detection theories and algorithms. Important conditions are firstly considered to categorize the large problem space of face detection. The conditions identified here are then represented as expressions so that developers can use them to express various problems. The expressed conditions and available face detection algorithms constitute the fuzzy inference rules and the Fuzzy Interpreter is constructed based on the rules. Once the conditions are expressed by developers, the Fuzzy Interpreter proposed take the role to inference the conditions and find and organize the optimal algorithms to solve the represented problem with corresponding conditions. A proof-of-concept is implemented and tested compared to conventional algorithms to show the performance of the proposed approach.
Keywords
Fuzzy Inference; Face Detection; Fuzzy Interpreter;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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