Journal of Systems Engineering and Electronics ›› 2006, Vol. 17 ›› Issue (1): 24-29.doi: 10.1016/S1004-4132(06)60005-4

• ELECTRONICS TECHNOLOGY • Previous Articles     Next Articles

Color-texture segmentation using JSEG based on Gaussian mixture modeling

Wang Yuzhong,  Yang Jie & Zhou Yue   

  1. Inst. of Image Processing and Pattern Recognition, Shanghai Jiaotong Univ. , Shanghai 200030, P. R. China
  • Online:2006-03-24 Published:2019-12-19

Abstract:

An improved approach for J-value segmentation (JSEG) is presented for unsupervised color image segmentation. Instead of color quantization algorithm, an automatic classification method based on adaptive mean shift (AMS) based clustering is used for nonparametric clustering of image data set. The clustering results are used to construct Gaussian mixture modelling (GMM) of image data for the calculation of soft / value. The region growing algorithm used in JSEG is then applied in segmenting the image based on the multiscale soft /-images. Experiments show that the synergism of JSEG and the soft classification based on AMS based clustering and GMM overcomes the limitations of JSEG successfully and is more robust.

Key words: color image segmentation, JSEG, adaptive mean shift based clustering, Gaussian mixture modeling, soft /-value