Image of Monolithic Circuit Segmentation Based on Watershed Algorithm

2013 ◽  
Vol 303-306 ◽  
pp. 1109-1113
Author(s):  
Zhu Lin Wang ◽  
Bin Fang ◽  
Xi Wei Guo
Keyword(s):  
Image Segmentation ◽  
Processing Method ◽  
Morphological Processing ◽  
Watershed Algorithm ◽  
Single Object ◽  
Watershed Transform ◽  
Key Technology ◽  
Processing Function ◽  
Important Position

Abstract. Image segmentation is a key technology in image engineering, it occupy an important position. This paper introduces the watershed transform to Image of monolithic circuit processing method, and then introduced the watershed transform to Image of monolithic circuit segmentation and sample. The results show that, by using the watershed algorithm and morphological processing function, which is connected with a plurality of object images are segmented into a plurality of single object, to achieve the image segmentation, and as far as possible to reduce or eliminate the phenomenon of over-segmentation. Finally it points out the further direction of research.

scholarly journals Universal void density profiles from simulation and SDSS

2014 ◽  
Vol 11 (S308) ◽  
pp. 542-545 ◽  
Author(s):  
S. Nadathur ◽  
S. Hotchkiss ◽  
J. M. Diego ◽  
I. T. Iliev ◽  
S. Gottlöber ◽  
...  
Keyword(s):  
Fundamental Property ◽  
Watershed Algorithm ◽  
Void Size ◽  
Self Similarity ◽  
Density Profiles ◽  
Watershed Transform ◽  
Future Studies ◽  
Main Galaxy ◽  
Wide Range ◽  
Self Similar

AbstractWe discuss the universality and self-similarity of void density profiles, for voids in realistic mock luminous red galaxy (LRG) catalogues from the Jubilee simulation, as well as in void catalogues constructed from the SDSS LRG and Main Galaxy samples. Voids are identified using a modified version of the ZOBOV watershed transform algorithm, with additional selection cuts. We find that voids in simulation areself-similar, meaning that their average rescaled profile does not depend on the void size, or – within the range of the simulated catalogue – on the redshift. Comparison of the profiles obtained from simulated and real voids shows an excellent match. The profiles of real voids also show auniversalbehaviour over a wide range of galaxy luminosities, number densities and redshifts. This points to a fundamental property of the voids found by the watershed algorithm, which can be exploited in future studies of voids.

scholarly journals A Multiobjective Piglet Image Segmentation Method Based on an Improved Noninteractive GrabCut Algorithm

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Feilong Kang ◽  
Chunguang Wang ◽  
Jia Li ◽  
Zheying Zong
Keyword(s):  
Image Segmentation ◽  
Real Time ◽  
Monitoring System ◽  
Structural Similarity ◽  
Morphological Processing ◽  
Video Monitoring ◽  
Segmentation Method ◽  
Time Requirements ◽  
And Behavior ◽  
Grabcut Algorithm

In the video monitoring of piglets in pig farms, study of the precise segmentation of foreground objects is the work of advanced research on target tracking and behavior recognition. In view of the noninteractive and real-time requirements of such a video monitoring system, this paper proposes a method of image segmentation based on an improved noninteractive GrabCut algorithm. The functions of preserving edges and noise reduction are realized through bilateral filtering. An adaptive threshold segmentation method is used to calculate the local threshold and to complete the extraction of the foreground target. The image is simplified by morphological processing; the background interference pixels, such as details in the grille and wall, are filtered, and the foreground target marker matrix is established. The GrabCut algorithm is used to split the pixels of multiple foreground objects. By comparing the segmentation results of various algorithms, the results show that the segmentation algorithm proposed in this paper is efficient and accurate, and the mean range of structural similarity is [0.88, 1]. The average processing time is 1606 ms, and this method satisfies the real-time requirement of an agricultural video monitoring system. Feature vectors such as edges and central moments are calculated and the database is well established for feature extraction and behavior identification. This method provides reliable foreground segmentation data for the intelligent early warning of a video monitoring system.

Research on Improved Methods of Watershed Algorithm

2013 ◽  
Vol 373-375 ◽  
pp. 583-586
Author(s):  
De Yong Wang ◽  
Ji Fan
Keyword(s):  
Watershed Algorithm ◽  
Normalized Cut ◽  
Watershed Transform ◽  
Cut Method ◽  
Weight Value ◽  
Area And Perimeter ◽  
The Common ◽  
Main Formula ◽  
Improved Methods ◽  
Image Segmentation Algorithm

In this paper an improved image segmentation algorithm based on watershed transform is presented. Firstly the normalized cut method and watershed transform are explained and analyzed. Secondly the idea of the improved algorithm and the main formula are explained. We consider the area and perimeter when we merge adjacent regions. We define a new weight value and discuss the value of the parameter αand β. Finally the experiment result is presented. The new algorithm reduces the nodes and the computational demand of the common normalized cut technique.

Improved watershed algorithm for color image segmentation

2009 ◽  
Author(s):  
Hong-bo Tan ◽  
Zhi-qiang Hou ◽  
Xiao-chun Li ◽  
Rong Liu ◽  
Wei-wu Guo
Keyword(s):  
Image Segmentation ◽  
Color Image ◽  
Color Image Segmentation ◽  
Watershed Algorithm
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