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Author Kato, Transformation Zoltan ♦ Kato, Zoltan ♦ Xiaowen, Ji ♦ Sziranyi, Tamas ♦ Toth, Zoltan ♦ Czuni, Laszlo
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Structural Property ♦ Retrieval Rate ♦ Stroke Parameter ♦ Stochastic Paintbrush Algorithm ♦ Traditional Feature ♦ Image Retrieval Method ♦ Applied Image Similarity Measure ♦ Color Content ♦ Paintbrush Stroke Parameter ♦ Painted Representation ♦ New Content ♦ Paintbrush Feature ♦ Painting Process ♦ Cbir Method ♦ Experimental Result ♦ Original Image
Description 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.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2002-01-01
Publisher Institution ICIP2002, Multimedia Retrieval and Applications, IEEE