A fast region segmentation algorithm on compressed gray images using Non-symmetry and Anti-packing Model and Extended Shading representation

2016 ◽  
Vol 34 ◽  
pp. 153-166 ◽  
Author(s):  
Yunping Zheng ◽  
Mudar Sarem
Keyword(s):  
Segmentation Algorithm ◽  
Region Segmentation ◽  
Packing Model ◽  
Fast Region

Regions Segmentation Algorithm of Triangle Meshes Based on Normal Vector

2010 ◽  
Vol 102-104 ◽  
pp. 111-115
Author(s):  
Jie Chen ◽  
Cheng Hui Gao ◽  
Bing Wei He
Keyword(s):  
Feature Extraction ◽  
Least Squares ◽  
Least Squares Method ◽  
Segmentation Algorithm ◽  
Normal Vector ◽  
Region Segmentation ◽  
Triangle Meshes ◽  
Normal Vectors

An approach of regions segmentation algorithm in triangle meshes based on threshold angle of the normal vectors is proposed. In this paper, a set of threshold angles is used to identify features and segment different surfaces, and then the non-feature regions based on least squares method are fitted and the corresponding fitting precision are obtained. Finally, the best threshold angle of each region is determined according to the comparison the above fitting precisions and each non-feature region points are obtained exactly. This method can improve the precision of feature extraction and region segmentation in some hybrid blend region. Examples are given to prove the effectiveness and the processing flexibility and stability of the proposed approach.

Split and Merge: A Region Based Image Segmentation

2018 ◽  
Vol 6 (8) ◽  
pp. 306 ◽  
Author(s):  
Anju Bala ◽  
Aman Kumar Sharma
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Digital Image Processing ◽  
Digital Image ◽  
Region Growing ◽  
Segmentation Algorithm ◽  
Region Segmentation ◽  
Segmentation Algorithms ◽  
Different Types ◽  
Split And Merge

Image segmentation is a very challenging task in digital image processing field. It is defined as the process of takeout objects from an image by dividing it into different regions where regions that depicts some information are called objects. There are different types of image segmentation algorithms. The segmentation process depends upon the type of description required for an application for which segmentation is to be performed. Hence, there is no universally accepted segmentation algorithm. Region segmentation is divided into three categories region growing, split and merge and watershed. But this study confines only to split and merge techniques. This paper includes split and merge approaches and their extended versions. This study highlights the main limitations and potentials of these approaches.

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