slugExpression Recognition System for Images Processing Using Interval Type2 Fuzzy Modeling

Abstract

face detection research confronts the full range of challenges found in general purpose, object class recognition. However, the class of faces also has very apparent regularities that are exploited by many heuristic or model - based methods or are readily “ learned” in data - driven methods. One expects some regularity when defining classes in general, but they may not be so apparent. Finally, though faces have tremendous within - class variability, face detection remains a two class recognition problem (face ver sus non face). The system correctly classified expressions for each individual using only still images. It distinguishes 3 expressions (Happiness (HA), surprise, anger, and fear) precisely and identifies 1 other, Happiness by the Average Recognition Rate accuracy of 85.25%. Also many people made mistake identifying surprise from happiness. According to Carlo research Surprise is mis - recognized as happy. Following this information, Output membership functions are built and clearly depicted some expressions due to the mentioned facts. Experimental results demonstrate the superiority of the proposed method to existing ones.

Authors and Affiliations

Bhagvat Jaiswal, Pramod Rajput, Dr. S. K. Shrivastava

Keywords

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  • EP ID EP18036
  • DOI -
  • Views 323
  • Downloads 11

How To Cite

Bhagvat Jaiswal, Pramod Rajput, Dr. S. K. Shrivastava (2014). slugExpression Recognition System for Images Processing Using Interval Type2 Fuzzy Modeling. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(5), -. https://europub.co.uk/articles/-A-18036