An Improved MeanShift Insulator Image Segmentation Algorithm

2013 ◽  
Vol 634-638 ◽  
pp. 3945-3949
Author(s):  
Fang Ting ◽  
Yun Biao Zhao ◽  
Xing Liu Hu ◽  
Xia Bing
Keyword(s):  
Image Segmentation ◽  
Hough Transform ◽  
Mean Shift ◽  
Detection Algorithm ◽  
Morphological Processing ◽  
Edge Detection Algorithm ◽  
Mean Shift Algorithm ◽  
Image Segmentation Algorithm

According to color characteristics of insulator ,The paper is based on HSI model and Mean Shift algorithm in order to segmentation insulator images. It firstly introduces theory of mean shift algorithm, then explains morphological processing with edge detection algorithm to extract the insulator images contour. Last using Hough transform to obtain the segmentation results. Experiment indicates that VC6.0 combined with opencv simulation the proposed algorithm could effectively extract segmentation of insulator images provides the basis for follow-up determination of insulator faults.

Research and Simulation on the Image Segmentation Algorithm with Corn Image Based on HSI Color Model

2012 ◽  
Vol 459 ◽  
pp. 128-131
Author(s):  
Xue Feng Hou ◽  
Yuan Yuan Shang
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Digital Image Processing ◽  
Detection Algorithm ◽  
Color Model ◽  
Edge Detection Algorithm ◽  
Segmentation Algorithms ◽  
Hsi Color Model ◽  
Classical Image ◽  
Image Segmentation Algorithm

Image segmentation is one focus of digital image processing. In this paper, fourteen different kinds of classical image segmentation algorithms are studied and compared using corn image and simulating in MATLAB based on HSI color model. The result reveals that the method that using H component based on HSI color model to deal with the histogram threshold algorithm and Laplace edge detection algorithm is effectively extract the plant from the corn image

AN EFFICIENT APPROACH TO COLOR IMAGE SEGMENTATION USING INTERMEDIATE FEATURES OF MAXIMUM OVERLAP WAVELET TRANSFORM IN PEAK FINDING ALGORITHM

2009 ◽  
Vol 09 (01) ◽  
pp. 67-76 ◽  
Author(s):  
S. VASUKI ◽  
L. GANESAN
Keyword(s):  
Image Segmentation ◽  
Wavelet Transform ◽  
Color Image ◽  
Mean Shift ◽  
Color Image Segmentation ◽  
Translation Invariance ◽  
Mean Shift Algorithm ◽  
Peak Finding ◽  
Transform Coefficients ◽  
Image Segmentation Algorithm

In this paper a novel color image segmentation algorithm based on homogeneity histogram is proposed. The proposed approach uses intermediate features of maximum overlap wavelet transform (IMOWT). The IMOWT, which is the efficient transform, has been applied to color image segmentation for its time effectiveness, flexibility and translation invariance which are required for good segmentation results. The set of transform coefficients derived from wavelet domain are subjected to an efficient peak finding algorithm (PFA). PFA is employed to identify the most significant peaks of the homogeneity histogram. While we process the homogeneity histogram, both local and global information are taken into account. This is particularly helpful in taking care of small objects and local variations of the image. This method provides better segmentation results when compared to the direct application of PFA and Mean shift algorithm.

Implementation of the parallel mean shift-based image segmentation algorithm on a GPU cluster

2018 ◽  
Vol 12 (3) ◽  
pp. 328-353 ◽  
Author(s):  
Fang Huang ◽  
Yinjie Chen ◽  
Li Li ◽  
Ji Zhou ◽  
Jian Tao ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Mean Shift ◽  
Segmentation Algorithm ◽  
Gpu Cluster ◽  
Image Segmentation Algorithm
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