Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique

Abstract

In this paper, an Eigenvector based system has been presented to recognize facial expressions from digital facial images. In the approach, firstly the images were acquired and cropping of five significant portions from the image was performed to extract and store the Eigenvectors specific to the expressions. The Eigenvectors for the test images were also computed, and finally the input facial image was recognized when similarity was obtained by calculating the minimum Euclidean distance between the test image and the different expressions.

Authors and Affiliations

Jeemoni Kalita, Karen Das

Keywords

Related Articles

Timed-Release Certificateless Encryption

Timed-Release Encryption(TRE) is an encryption mechanism that allows a receiver to decrypt a ciphertext only after the time that a sender designates. In this paper, we propose the notion of Timed-Release Certificateless...

Evaluating Web Accessibility Metrics for Jordanian Universities

University web portals are considered one of the main access gateways for universities. Typically, they have a large candidate audience among the current students, employees, and faculty members aside from previous and f...

Air Pollution Analysis using Ontologies and Regression Models

Rapidly throughout the world economy, "the expansive Web" in the "world" explosive growth, rapidly growing market characterized by short product cycles exists and the demand for increased flexibility as well as the exten...

Role of Knowledge Reusability in Technological Environment During Learning

Role of technology and reusability on the knowledge management and knowledge transformation has been analyzed by considering the extended model of Nonaka and Takeuchi which includes the knowledge reuse in the three dimen...

Examining the Impact of Feature Selection Methods on Text Classification

Feature selection that aims to determine and select the distinctive terms representing a best document is one of the most important steps of classification. With the feature selection, dimension of document vectors are r...

Download PDF file
  • EP ID EP135713
  • DOI 10.14569/IJACSA.2013.040229
  • Views 74
  • Downloads 0

How To Cite

Jeemoni Kalita, Karen Das (2013). Recognition of Facial Expression Using Eigenvector Based Distributed Features and Euclidean Distance Based Decision Making Technique. International Journal of Advanced Computer Science & Applications, 4(2), 196-202. https://europub.co.uk/articles/-A-135713