An Image Segmentation Algorithm in Image Processing Based on Threshold Segmentation

2007 ◽  
Author(s):  
Shiping Zhu ◽  
Xi Xia ◽  
Qingrong Zhang ◽  
Kamel Belloulata
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Segmentation Algorithm ◽  
Threshold Segmentation ◽  
Image Segmentation Algorithm

An Improved Otsu Image Segmentation Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 3751-3754
Author(s):  
Yan Xue Dong
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Gaussian Noise ◽  
Segmentation Algorithm ◽  
Small Object ◽  
Image Segmentation Algorithm ◽  
Threshold Point

Otsu segmentation algorithm is one of the most successful algorithms in the field of image processing,However, it has drawbacks such as it is poor in dividing small object in images. This paper propose a improved Otsu algorithm based on weighted smooth histogram which can ensure the location of threshold point is more near to the valley point of the image and at the same time ensure the ensure between-class variance maximum.The results show that the improved Otsu algorithm can effectively accomplish segmentation for multimodal image, and get better segmentation results for images added Gaussian noise.

Evaluation and Research on Block-Division Based Image Segmentation Algorithm

2014 ◽  
Vol 525 ◽  
pp. 723-726
Author(s):  
Yu Bing Dong ◽  
Ming Jing Li ◽  
Ying Sun
Keyword(s):  
Image Segmentation ◽  
Segmentation Algorithm ◽  
Experimental Results ◽  
The Other ◽  
Image Recovery ◽  
Threshold Method ◽  
Threshold Segmentation ◽  
Segmentation Algorithms ◽  
Image Segmentation Algorithm

The block-division based segmentation algorithm is raised in this paper, which overcomes the shortcomings of the whole and single threshold method. Each block is processed with two-value segmentation algorithm, and finally, all blocks are combined for image recovery. In order to evaluate the performance of block-division based segmentation algorithms, some experiments are carried out by using Matlab 7.0. Experimental results show that block-division based segmentation algorithms can perform well and get a better result than the other threshold segmentation algorithms.

scholarly journals An improved image segmentation algorithm based on the maximum class variance method

2020 ◽  
Vol 309 ◽  
pp. 03029
Author(s):  
Qianhui Qi ◽  
Yimin Tian ◽  
Lili Han
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Optimization Theory ◽  
Segmentation Algorithm ◽  
Segmentation Method ◽  
Variance Method ◽  
Optimal Segmentation ◽  
Image Segmentation Algorithm ◽  
Cuckoo Algorithm

Image segmentation is an important part of image processing. The result of image segmentation directly affects the effect of subsequent image processing. However the efficiency of the traditional maximum class variance method is low. This paper uses the cuckoo algorithm to optimize the traditional maximum class variance method to achieve a better segmentation effect. This image segmentation method combined with optimization theory can achieve the purpose of finding the optimal segmentation.

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