An algorithm for unsupervised color image segmentation

Author

Lucchese, L. ; Mitra, S.K.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Santa Barbara, CA, USA

fYear

1998

fDate

7-9 Dec 1998

Firstpage

33

Lastpage

38

Abstract

In a great number of fields of computer vision image segmentation plays an essential role as a preliminary step towards further and higher levels of image processing. An original algorithm for unsupervised segmentation of color images is here presented; it resorts to a palletized representation of images, it uses the low spatial frequency content of color which is represented in the CIELUV space and in this space it builds and thresholds hue and chroma histograms finding out the color clusters which allow the image to be segmented. Evidence of the algorithm´s effectiveness is reported

Keywords

computer vision; image colour analysis; image representation; image segmentation; unsupervised learning; CIELUV space; chroma histogram; color clusters; computer vision image segmentation; histograms thresholding; hue histogram; image processing; low spatial frequency content; palletized representation; unsupervised algorithm; unsupervised color image segmentation; video sequences; Clustering algorithms; Color; Computer vision; Frequency estimation; Histograms; Image processing; Image segmentation; Pixel; Software libraries; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Signal Processing, 1998 IEEE Second Workshop on

Conference_Location

Redondo Beach, CA

Print_ISBN

0-7803-4919-9

Type

conf

DOI

10.1109/MMSP.1998.738909

Filename

738909