Segmentation Methods Based On Logistic Type Mixture Model

This Book contributes analysis and development of image segmentation algorithms based on finite logistic type mixture models. These techniques are much useful in a variety of applications such as medical images, filming, and video, security surveillance, face recognition, gesture analysis. Image segmentation is a prerequisite for computer vision and human-computer interactions. Image segmentation is an important domain of research in computer science and allied areas due to its ready applicability in designing and developing several systems. The image segmentation is a process in which the pixels in the image are grouped such that they form a number of meaningful regions that are homogeneous within the regions, heterogeneous between the regions. Several image segmentation techniques have been developed with various considerations. A comparative study is carried with developed algorithms and with earlier existing models based on image segmentation algorithm with Gaussian mixture model. It is observed that the three-parameter logistic type mixture model with hierarchical clustering algorithm better than that of a Gaussian mixture model with K-means and two-parameter logistic type.

Author: Venkata Satyanarayana Kalahasthi

Publisher: LAP Lambert Academic Publishing

Publication Date: Dec 28, 2020

Number of Pages: 188 pages

Binding: Paperback or Softback

ISBN-10: 6203199044

ISBN-13: 9786203199048