Genetic Learning for Adaptive Image Segmentation

Released on by Bir Bhanu
preview-18

  • Genetic Learning for Adaptive Image Segmentation Book Detail

  • Author : Bir Bhanu
  • Release Date : 2012-12-06
  • Publisher : Springer Science & Business Media
  • Genre : Computers
  • Pages : 283
  • ISBN 13 : 1461527740
  • File Size : 97,97 MB
DOWNLOAD BOOK

Genetic Learning for Adaptive Image Segmentation by Bir Bhanu PDF Summary

Book Description: Image segmentation is generally the first task in any automated image understanding application, such as autonomous vehicle navigation, object recognition, photointerpretation, etc. All subsequent tasks, such as feature extraction, object detection, and object recognition, rely heavily on the quality of segmentation. One of the fundamental weaknesses of current image segmentation algorithms is their inability to adapt the segmentation process as real-world changes are reflected in the image. Only after numerous modifications to an algorithm's control parameters can any current image segmentation technique be used to handle the diversity of images encountered in real-world applications. Genetic Learning for Adaptive Image Segmentation presents the first closed-loop image segmentation system that incorporates genetic and other algorithms to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions, such as time of day, time of year, weather, etc. Image segmentation performance is evaluated using multiple measures of segmentation quality. These quality measures include global characteristics of the entire image as well as local features of individual object regions in the image. This adaptive image segmentation system provides continuous adaptation to normal environmental variations, exhibits learning capabilities, and provides robust performance when interacting with a dynamic environment. This research is directed towards adapting the performance of a well known existing segmentation algorithm (Phoenix) across a wide variety of environmental conditions which cause changes in the image characteristics. The book presents a large number of experimental results and compares performance with standard techniques used in computer vision for both consistency and quality of segmentation results. These results demonstrate, (a) the ability to adapt the segmentation performance in both indoor and outdoor color imagery, and (b) that learning from experience can be used to improve the segmentation performance over time.

Disclaimer: www.yourbookbest.com does not own Genetic Learning for Adaptive Image Segmentation books pdf, neither created or scanned. We just provide the link that is already available on the internet, public domain and in Google Drive. If any way it violates the law or has any issues, then kindly mail us via contact us page to request the removal of the link.

Soft Computing for Image Processing

Soft Computing for Image Processing

File Size : 23,23 MB
Total View : 1366 Views
DOWNLOAD

Any task that involves decision-making can benefit from soft computing techniques which allow premature decisions to be deferred. The processing and analysis of

Applications of Evolutionary Computing

Applications of Evolutionary Computing

File Size : 66,66 MB
Total View : 7475 Views
DOWNLOAD

This book constitutes the refereed proceedings of five application-oriented workshops held concurrently as EvoWorkshops 2001 in Como, Italy in April 2001. The 5

Data Mining: A Heuristic Approach

Data Mining: A Heuristic Approach

File Size : 28,28 MB
Total View : 3618 Views
DOWNLOAD

Real life problems are known to be messy, dynamic and multi-objective, and involve high levels of uncertainty and constraints. Because traditional problem-solvi

Genetic Programming III

Genetic Programming III

File Size : 83,83 MB
Total View : 6030 Views
DOWNLOAD

Genetic programming (GP) is a method for getting a computer to solve a problem by telling it what needs to be done instead of how to do it. Koza, Bennett, Andre