scholarly journals The Application of Threshold Segmentation Algorithm in Loess Microstructure Image Analysis

2012 ◽  
Author(s):  
Nian-dong Deng ◽  
Xiao Wang ◽  
Feng Wang ◽  
Yang Zhou
Keyword(s):  
Image Analysis ◽  
Segmentation Algorithm ◽  
Threshold Segmentation

The Detection Method of Lane Line Based on the Improved Otsu Threshold Segmentation

2015 ◽  
Vol 741 ◽  
pp. 354-358 ◽  
Author(s):  
Yang Shan Tang ◽  
Dao Hua Xia ◽  
Gui Yang Zhang ◽  
Li Na Ge ◽  
Xin Yang Yan
Keyword(s):  
Image Segmentation ◽  
Processing Time ◽  
Detection Method ◽  
Segmentation Algorithm ◽  
Test Results ◽  
Threshold Segmentation ◽  
Otsu Method ◽  
Time Requirements ◽  
Lane Line ◽  
Center Distance

For overcoming the shortage of Otsu method, proposed an improved Otsu threshold segmentation algorithm. On the basis of Otsu threshold segmentation algorithm, the gray level was divided into two classes according to the image segmentation, to determine the best threshold by comparing their center distance, so as to achieve peak line recognition under the condition of multiple gray levels. Then did experiments on image segmentation of the lane line with MATLAB by traditional Otsu threshold segmentation algorithm and the improved algorithm, the threshold of traditional Otsu threshold segmentation algorithm is 144 and the threshold of the improved Otsu threshold segmentation algorithm is 131, the processing time is within 0.453 s. Test results show that the white part markings appear more, the intersection place of white lines and the background is more clear, so this method can identify lane markings well and meet the real-time requirements.

Image Threshold Segmentation Algorithm Based on Histogram Statistical Property

2014 ◽  
Vol 644-650 ◽  
pp. 4027-4030
Author(s):  
Hong Li ◽  
Zhong An Lai ◽  
Jun Wei Lei
Keyword(s):  
Normal Distribution ◽  
Complex Shape ◽  
Good Method ◽  
Segmentation Algorithm ◽  
Gray Level ◽  
Background Region ◽  
Threshold Segmentation ◽  
Target Region ◽  
Statistical Property ◽  
Otsu’S Method

The traditional Otsu threshold algorithm is not a good method for processing the real images because of complex shape and unbalanced distribution. To solve this problem, the paper uses the thinking of Otsu’s method for reference, introduces a threshold segmentation algorithm based on histogram statistical property. In addition, the paper draws a comparison between the new algorithm and Otsu’s algorithm. Experimental results show that the new algorithm can get better segmentation effect than that of Otsu’s method when the gray-level distribution of the background follows normal distribution approximatively, and the target region is less than the background region.

Review of Otsu Segmentation Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 1959-1961 ◽  
Author(s):  
Yan Xue Dong
Keyword(s):  
Image Processing ◽  
Image Analysis ◽  
Image Segmentation ◽  
Simple Calculation ◽  
Segmentation Algorithm ◽  
Image Thresholding ◽  
Otsu Method

Image segmentation is the key step in the process from image processing to image analysis. Otsu method is one of the most successful methods for image thresholding because of its simple calculation. Otsu method can select threshold automatically and divide the object from the background in the image. In this paper, various Otsu algorithm are studied.

scholarly journals Implementation of Watershed Based Image Segmentation Algorithm using Distance Transform for Grid Computing

2013 ◽  
Vol 10 (6) ◽  
pp. 1715-1719
Author(s):  
Megha Sharma ◽  
Seema Verma
Keyword(s):  
Image Analysis ◽  
Image Segmentation ◽  
Grid Computing ◽  
Segmentation Algorithm ◽  
New Method ◽  
Distance Transform ◽  
Image Information ◽  
Watershed Transform ◽  
Image Segmentation Algorithm

A new method for image segmentation using watershed transform algorithm is presented in this paper. It takes advantage of the fact that the proposed algorithm produced good results even if the same parameters are used for the standard segmentation algorithm. The proposed segmentation algorithm will be very effective for grid computing as it seems to possess specific tasks of image information and detection in order to obtain a detailed and accurate image analysis.

Sign in / Sign up

Export Citation Format

Share Document