Image Histogram Segmentation by Multi-Level Thresholding using Hill Climbing Algorithm
Sayantan Nath, Sonali Agarwal, Abbas Kazmi Qasima · 2011
Image Segmentation is as essential technique in image processing area to distinguish important object from unnecessary background substrates. Most of the image segmentation methods are based on the “Cloud Histogram ” or Density Variation Concept which cannot be capable to work with individual value of the histogram of image. The “Hill Climbing ” based Multilevel Thresholding technique will overcome the limitation and it is applicable to the value of image histogram directly to recognize the absolute pitch point turn over. This technique is based on individual value of histogram column. The highest folds of the image histogram curve play a major role in graphical resolution and visual orientation. This research perspective is not given importance in the field of histogram clustering yet.