Image description with local patterns: An application to face recognition

Wei Zhou, Alireza Ahrary, Sei Ichiro Kamata

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

In this paper, we propose a novel approach for presenting the local features of digital image using 1D Local Patterns by Multi-Scans (1DLPMS). We also consider the extentions and simplifications of the proposed approach into facial images analysis. The proposed approach consists of three steps. At the first step, the gray values of pixels in image are represented as a vector giving the local neighborhood intensity distrubutions of the pixels. Then, multi-scans are applied to capture different spatial information on the image with advantage of less computation than other traditional ways, such as Local Binary Patterns (LBP). The second step is encoding the local features based on different encoding rules using 1D local patterns. This transformation is expected to be less sensitive to illumination variations besides preserving the appearance of images embedded in the original gray scale. At the final step, Grouped 1D Local Patterns by Multi-Scans (G1DLPMS) is applied to make the proposed approach computationally simpler and easy to extend. Next, we further formulate boosted algorithm to extract the most discriminant local features. The evaluated results demonstrate that the proposed approach outperforms the conventional approaches in terms of accuracy in applications of face recognition, gender estimation and facial expression.

Original languageEnglish
Pages (from-to)1494-1505
Number of pages12
JournalIEICE Transactions on Information and Systems
VolumeE95-D
Issue number5
DOIs
Publication statusPublished - 2012 May

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Keywords

  • 1DLPMS
  • Face recognition
  • G1DLPMS
  • Gender estimation
  • Local presentation
  • Multiscans

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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