Image segmentation is the process of dividing an image into homogenous regions. It is an essential step
towards high-level image processing task such as image analysis, pattern recognition and computer vision. Processing
of color images has become an important issue due to its huge usage in computer vision applications. It is observed that
most of the color image segmentation techniques are derived from monochrome image segmentation. The techniques
for segmentation of monochrome images are based on the principles of histogram thresholding, edge detection, region
growing etc. Many color image segmentation algorithms using different color models and these principles are proposed.
Extraction of objects within an image without a prior knowledge is one of the important issues in segmentation area.
Novel approaches such as fuzzy set theory, neural network and neuro-fuzzy based segmentation are coming up to tackle
this problem. This paper is an endeavor to review various algorithms and recent advances in color image segmentation.
Kanchan Subhash Deshmukh,
"Color image segmentation: a review", Proc. SPIE 7546, Second International Conference on Digital Image Processing, 754624 (26 February 2010); doi: 10.1117/12.856011; https://doi.org/10.1117/12.856011