scholarly journals Infrared image-based detection method of electrical equipment overheating area in substation

2020 ◽  
Vol 185 ◽  
pp. 01034
Author(s):  
Songhai Fan ◽  
Tianyu Li ◽  
Yicen Liu ◽  
Yiyu Gong ◽  
Kunjian Yu
Keyword(s):  
Active Contour ◽  
Clustering Algorithm ◽  
Active Contour Model ◽  
Infrared Image ◽  
Electrical Equipment ◽  
Detection Algorithm ◽  
Target Area ◽  
Detection Range ◽  
Edge Points ◽  
Fcm Clustering

For the detection of overheated areas of electrical equipment, in order to accurately segment out the overheated areas and reduce the fault detection range, this paper proposes a new overheated area detection algorithm. Firstly, the Ostu algorithm is used to remove the background and segment the general area of the electrical equipment area; secondly, the active contour model is used to refine the edge of the target area to remove the redundant edge points; finally, FCM clustering algorithm is used to suppress over segmentation and accurately divide the overheated area. The experiment proves that the algorithm can accurately divide the overheated area, and has certain practical value.

An Image Segmentation Method of Underwater Targets Based on Active Contour Model

2014 ◽  
Vol 511-512 ◽  
pp. 457-461
Author(s):  
Tao Liu ◽  
Lei Wan ◽  
Xing Wei Liang
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Active Contour Model ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Segmentation Method ◽  
Contour Model ◽  
Underwater Targets ◽  
Underwater Target ◽  
Images Processing

The underwater images are disturbed with low signal to noise ratio and edge blur, because there are the light scattering and absorption effects. If the traditional thresholding method is used directly to segment underwater images, it will usually lead to be less effective to process underwater images. An image segmentation method of underwater target based on active contour model was proposed in this paper. Firstly, using Canny edge detection algorithm to detect the edges of the original image to obtain the information of a crude outline, then the algorithm based on C-V active contour model to segment underwater target images was addressed. The images processing results based on threshold segmentation method and C-V model method were compared. Experiments demonstrate the effectiveness of the proposed algorithm for underwater targets images segmentation.

Heuristic Initialization for Active Contour Models in CT/MRI Image Processing

2015 ◽  
Vol 15 (03) ◽  
pp. 1550010
Author(s):  
Hao Liu ◽  
Hongbo Qian ◽  
Ning Dai ◽  
Jianning Zhao
Keyword(s):  
Active Contour ◽  
Active Contour Model ◽  
Heuristic Method ◽  
Initial Contour ◽  
Active Contour Models ◽  
Contour Model ◽  
Segmentation Approach ◽  
Edge Points ◽  
Contour Models ◽  
Level Set Evolution

It is an important segmentation approach of CT/MRI images to automatically extract contours in every slice using active contour models. The key point of the segmentation approach is to automatically construct initial contours for active contour models because any active contour model is sensitive to its initial contour. This paper presents an algorithm to construct such initial contours using a heuristic method. Assume that the contour in previous slice (previous contour) is accurate. The contour in the current slice (current contour) is constructed according to the previous contour using the way: Recognition and link of edge points of tissues according to the previous contour. The contour linking edge points is used as the initial contour of the distance regularized level set evolution (DRLSE) method and then an accurate contour can be extracted in the current slice.

A Novel Flame Edge Detection Algorithm via A Novel Active Contour Model

2016 ◽  
Vol 9 (9) ◽  
pp. 275-282 ◽  
Author(s):  
Wanli Feng ◽  
Ying Li ◽  
Shangbing Gao ◽  
Yunyang Yan ◽  
Jianxun Xue
Keyword(s):  
Edge Detection ◽  
Active Contour ◽  
Active Contour Model ◽  
Detection Algorithm ◽  
Edge Detection Algorithm ◽  
Contour Model

scholarly journals Efficient Active Contour and K-Means Algorithms in Image Segmentation

2004 ◽  
Vol 12 (2) ◽  
pp. 101-120 ◽  
Author(s):  
J.R. Rommelse ◽  
H.X. Lin ◽  
T.F. Chan
Keyword(s):  
Image Segmentation ◽  
Active Contour ◽  
Clustering Algorithm ◽  
Active Contour Model ◽  
Asynchronous Communication ◽  
Synchronous Communication ◽  
Image Domain ◽  
Parallel Efficiency ◽  
Contour Model ◽  
Segmentation Algorithms

In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed active contour image segmentation model. We propose integrating aspects of the classic algorithm to improve the active contour model. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.

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