Optimal partitioning methods for image segmentation

The Journal of Engineering

Shreyas Fadnavis¹ 

[1] Computer Engineering, Pune Institute of Computer Technology, Pune, India

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

DOI  :  10.1049/joe.2015.0171

学科分类：工程和技术（综合）

来源: IET

【 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】

CC BY