Abstract:
Color image segmentation and texture classification are challenging tasks
in image analysis. This thesis presents novel techniques for color image
segmentation and texture classification using soft computing methodologies.
The mathematical foundation of Histon has been presented here. The histon
is a contour plotted on the top of the histograms of the primary color com-
ponents of a color image. It exploits the correlation among the neighboring
pixels in the same plane as well as the other color planes. The concept of
roughness index has been introduced to correlate the histogram and the his-
ton. The roughness index plotted against the intensity, exhibits crests and
troughs similar to the histogram with well defined peak and valley points.
The proposed color thresholding algorithm based on the histon roughness
index, yields considerable improvements in the segmentation performance
when compared with other conventional techniques.
