Research on Color Image Classification Based on HSV Color Space

Author

Chen Junhua ; Lei Jing

Author_Institution

Sch. of Math. & Comput. Sci., Yunnan Nat. Univ., Kunming, China

fYear

2012

fDate

8-10 Dec. 2012

Firstpage

944

Lastpage

947

Abstract

According to color image data structure to adapt to the image into the HSV model of the human visual system components, and extract the H component. The hue H of HSV color space is the most important resolution of visual features, therefore we use Contourlet transform to deal with hue H components, extract the third factor features as semantic features of image classification, then use SVM classifier to classify images. The experimental results show that this method has better classification results.

Keywords

data structures; feature extraction; image classification; image colour analysis; transforms; H component extraction; HSV color space; color image classification; color image data structure; contourlet transform; human visual system components; semantic features; visual features; Feature extraction; Gray-scale; Image classification; Image color analysis; Semantics; Support vector machines; Transforms; Contourlet transform; HSV color space; SVM; classifier; color image; low frequency coefficients;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation, Measurement, Computer, Communication and Control (IMCCC), 2012 Second International Conference on

Conference_Location

Harbin

Print_ISBN

978-1-4673-5034-1

Type

conf

DOI

10.1109/IMCCC.2012.226

Filename

6429061