Content-based image retrieval using stochastic paintbrush transformation

Zoltan Kato, Xiaowen Ji, Tamas Sziranyi, Zoltan Toth, Laszlo Czuni

Research output: Contribution to conferencePaper

5 Citations (Scopus)


Herein, we propose a new content based image retrieval method. The novelty of our approach lies in the applied image similarity measure: Unlike traditional features like color, texture or shape, our measure is based on a painted representation of the original image. We use paintbrush stroke parameters as features. These strokes are produced by a stochastic paintbrush algorithm which simulates a painting process. Stroke parameters include color, orientation and location. Therefore, it provides information not only about the color content but also about the structural properties of an images. Experimental results on a database of more than 500 images show that the CBIR method using paintbrush features has higher retrieval rate than methods using color features only.

Original languageEnglish
Publication statusPublished - Jan 1 2002
EventInternational Conference on Image Processing (ICIP'02) - Rochester, NY, United States
Duration: Sep 22 2002Sep 25 2002


OtherInternational Conference on Image Processing (ICIP'02)
CountryUnited States
CityRochester, NY


ASJC Scopus subject areas

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

Cite this

Kato, Z., Ji, X., Sziranyi, T., Toth, Z., & Czuni, L. (2002). Content-based image retrieval using stochastic paintbrush transformation. I/944-I/947. Paper presented at International Conference on Image Processing (ICIP'02), Rochester, NY, United States.