Feature guide: A statistically based feature selection scheme

Jia You, T. Dillon, E. Pissaloux

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

This paper presents a new approach to content-based image retrieval by addressing three primary issues: image feature extraction and representation, similarity measure, and search methods. A statistically based feature selection scheme is introduced to guide the selection of the most appropriate image features for dynamic image indexing and similarity measures. In addition, a fractional discrimination function is proposed to enhance image feature points in conjunction with image decomposition and contextual filtering for image classification. Furthermore, a feature component code is used to facilitate the hierarchical search for the best matching, where images are queried by different features or combinations. The experimental results demonstrate the effectiveness of the proposed method.
Original languageEnglish
Title of host publicationIEEE International Conference on Image Processing
Pages717-720
Number of pages4
Publication statusPublished - 1 Jan 2001
Externally publishedYes
EventIEEE International Conference on Image Processing (ICIP) - Thessaloniki, Greece
Duration: 7 Oct 200110 Oct 2001

Conference

ConferenceIEEE International Conference on Image Processing (ICIP)
CountryGreece
CityThessaloniki
Period7/10/0110/10/01

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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