Optimal partitioning methods for image segmentation

The Journal of Engineering

Shreyas Fadnavis¹ 

[1] Pune Institute of Computer Technology;

关键词: image segmentation;    image colour analysis;    image noise level;    image intensity;    image colour;    sample image;    image thresholding;    image growing;    image merging;    image splitting;    digital image processing;    video surveillance systems;    weather prediction;    astronomy;    medical science;    image segmentation;    optimal partitioning methods;   

DOI  :  10.1049/joe.2015.0171

来源: DOAJ

【 摘 要 】

The importance of image processing is increasing in the digitally connected world due to its numerous applications in various fields of medical science, astronomy, weather prediction and video surveillance systems etc. The latest research and development in this field has helped the authors to obtain finer details of a particular image under study. The image segmentation technique, a part of digital image processing, helps to obtain meaningful information of the object. This study discusses the three widely used important image segmentation techniques: namely, split and merge, image growing and thresholding and their effects on a sample image. The authors results thus depict a significant difference in the segmented image by split and merge, image growing and thresholding. Split and merge is the optimal method of image segmentation as compared with the other two techniques mentioned above. The choice of the method varies with type of image, its colour, intensity and noise level.

【 授权许可】

Unknown