A linear manifold color descriptor for medicine package recognition

Kenjiro Sugimoto, Koji Inoue, Yoshimitsu Kuroki, Sei Ichiro Kamata

Research output: Contribution to journalArticle

Abstract

This paper presents a color-based method for medicine package recognition, called a linear manifold color descriptor (LMCD). It describes a color distribution (a set of color pixels) of a color package image as a linear manifold (an affine subspace) in the color space, and recognizes an anonymous package by linear manifold matching. Mainly due to low dimensionality of color spaces, LMCD can provide more compact description and faster computation than description styles based on histogram and dominant-color. This paper also proposes distance-based dissimilarities for linear manifold matching. Specially designed for color distribution matching, the proposed dissimilarities are theoretically appropriate more than J-divergence and canonical angles. Experiments on medicine package recognition validates that LMCD outperforms competitors including MPEG-7 color descriptors in terms of description size, computational cost and recognition rate.

Original languageEnglish
Pages (from-to)1264-1271
Number of pages8
JournalIEICE Transactions on Information and Systems
VolumeE95-D
Issue number5
DOIs
Publication statusPublished - 2012 May

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Keywords

  • Linear manifold
  • Low-level color descriptor
  • Medicine package recognition

ASJC Scopus subject areas

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

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