Quadrant based vertical distance method for face shape representation

Research output: Contribution to journalArticlepeer-review

Abstract

To measure similarity between face shapes, quadrant based vertical distance method is proposed. The face shape curve is divided into 4 quadrants with the centroid of the curve as origin. The face shape curve on each quadrant is represented with a list of the distance of any boundary point on the quadrant to horisontal axis of the same quadrant. The nearest point from vertical axis at each quadrant is choosen as starting point to obtain rotation invariant. This representation aimed to describe dominant characteristic of face shape curve represented by the curvature of curve at upside and downside. To measure similarity between shape representation, a Fuzzy Euclidean distance method is proposed. A zmf membership function is used to map the Euclidean distance of 2 descriptor's components to certain similarity value [0, 1]. Experimental result on 345 faces shows that quadrant based vertical distance method is more efficient and gives average precision 28% improved than those of the conventional method. This result shows that the proposed method is promising to be used for face retrieval and recognition system.

Original languageEnglish
Pages (from-to)25-31
Number of pages7
JournalInternational Journal of Soft Computing
Volume4
Issue number1
Publication statusPublished - 24 Mar 2009

Keywords

  • Face shape
  • Fuzzy euclidean distance
  • Fuzzy similarity measure
  • Quadrant based vertical distance method

Fingerprint

Dive into the research topics of 'Quadrant based vertical distance method for face shape representation'. Together they form a unique fingerprint.

Cite this