Open AccessResearch and analysis of threshold segmentation algorithms in image processing
Author(s) -
Zuodong Niu,
Handong Li
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022122
Subject(s) - segmentation based object categorization , scale space segmentation , image segmentation , segmentation , artificial intelligence , computer science , region growing , minimum spanning tree based segmentation , image processing , digital image processing , computer vision , process (computing) , range segmentation , algorithm , pattern recognition (psychology) , image (mathematics) , operating system
Image segmentation is one of the most difficult and important tasks in digital image processing. The accuracy and effect of segmentation determine the final success or failure of the calculation and analysis process. Therefore, analysis and improvement on basic image segmentation algorithms should be paid attention to in a quite wide range of applications. This paper mainly introduces and studies the principle and characteristics of threshold segmentation algorithm, and analyses the application scenarios of global threshold segmentation and adaptive local threshold segmentation related algorithms, which has certain reference significance for digital image processing related research.