Phase Image Segmentation and Filtering Algorithm Based on Direction of the Gradient Factor

2014 ◽  
Vol 670-671 ◽  
pp. 1488-1492
Author(s):  
Chi Zhang ◽  
Zhong Wei Li ◽  
Yu Sheng Shi
Keyword(s):  
Image Segmentation ◽  
Median Filter ◽  
Phase Image ◽  
Point Matching ◽  
Performance Specifications ◽  
Noise Data ◽  
Image Edge ◽  
Phase Data ◽  
Effective Phase ◽  
Phase Shift Method

To satisfy rigid performance specifications of structure light measurement by phase shift method, the algorithm of phase image segmentation and filter based on direction of the gradient factor was introduced in this paper. In this method, phase image was divided into three parts by condition of extreme value and direction of the gradient factor, including continuous area, edge area and regional noise. Only phase data in continuous area was processed by median filter. This method can reduce the point matching computation of 3-D reconstruction, and at the same time can protect the image edge details, so as to reduce the noise data, provide accurate and effective phase data for reconstruction. Results of segmentation verify feasibility and effectiveness of presented method.

Weighted variational two-phase image segmentation based on Fuzzy Region Competition

2011 ◽  
Author(s):  
Vinicius R. P. Borges ◽  
Celia A. Zorzo Barcelos ◽  
Denise Guliato ◽  
Marcos Aurelio Batista
Keyword(s):  
Image Segmentation ◽  
Phase Image ◽  
Two Phase ◽  
Fuzzy Region

Application of Petrochemical Heat Equipments' State Inspection Based on the Edge Detection of Infrared Image Segmentation

2013 ◽  
Vol 303-306 ◽  
pp. 970-974
Author(s):  
Lin Lin Cui ◽  
Hua Lai ◽  
Yong Wang Tang ◽  
Ming Jie Qi
Keyword(s):  
Image Segmentation ◽  
Edge Detection ◽  
Infrared Image ◽  
Threshold Value ◽  
State Inspection ◽  
Experimental Result ◽  
Target Area ◽  
Image Edge ◽  
Roberts Operator ◽  
Infrared Image Segmentation

According to the problem of petrochemical heat equipment status inspection and fault diagnosis, a method based on edge detection of infrared image segmentation was presented studying the infrared image segmentation based on edge detection and combining Roberts operator into best threshold segmentation method to do simulation of buoyant, medium and heavy damaged equipments. Experimental result shows that edge detection operator of best threshold value has ideal effects to the image edge extraction's target area of thermal infrared equipment.

scholarly journals Algorithmic Approaches For Image Edge Detection

2021 ◽  
Vol 10 (3) ◽  
pp. 1942-1948
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Edge Detection ◽  
Image Enhancement ◽  
Digital Image Processing ◽  
Digital Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Algorithmic Approaches

Edge detection is most important technique in digital image processing. It play an important role in image segmentation and many other applications. Edge detection providesfoundation to many medical and military applications.It difficult to generate a generic code for edge detection so many kinds ofalgorithms are available. In this article 4 different approaches Global image enhancement with addition (GIEA), Global image enhancement with Multiplication (GIEM),Without Global image enhancement with Addition (WOGIEA),and without Global image enhancement with Multiplication (WOGIEM)for edge detection is proposed. These algorithms are validatedon 9 different images. The results showthat GIEA give us more accurate results as compare to other techniques.

Multi-phase image segmentation with the adaptive deformable mesh

2019 ◽  
Vol 117 ◽  
pp. 97-103 ◽  
Author(s):  
Tuan T. Nguyen ◽  
Vedrana A. Dahl ◽  
J. Andreas Bærentzen
Keyword(s):  
Image Segmentation ◽  
Phase Image ◽  
Deformable Mesh ◽  
Multi Phase

Seeds Microscopic Image Edge Detection Based on the Clustering Method and Applied in Andriod Platform

2014 ◽  
Vol 644-650 ◽  
pp. 1100-1103
Author(s):  
Xiao Fen Guo ◽  
Yan Li Zuo
Keyword(s):  
Clustering Algorithm ◽  
Median Filter ◽  
Threshold Value ◽  
Microscopic Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Hierarchical Clustering Algorithm ◽  
Edge Based ◽  
Roberts Operator ◽  
Suppress Noise

Sobel, Roberts operator is derived based on the differential. As a result of the template and fixed threshold value, it lacks adaptability. Median filter on images of the collected cardiac seeds maturity, use split clustering algorithm on cardiac seeds maturity for the first image gradient value clustering, condensed cluster on the result of the first split the clustering results, then secondly division cluster, and finally work out the image edge based on the second clustering results and realize on the FPGA implementation. At last the method is Applied in Andriod Platform. The experimental results show that it is more delicate to use the hierarchical clustering algorithm to detect the edge and it has stronger ability to suppress noise.

Algorithm for Improving Image Edge Detection Based on Directional Wavelet Transform

2014 ◽  
Vol 543-547 ◽  
pp. 2763-2765
Author(s):  
Xiang Shi Wang ◽  
Gui Feng Liu
Keyword(s):  
Wavelet Transform ◽  
Edge Detection ◽  
Median Filter ◽  
Image Data ◽  
Edge Image ◽  
Image Edge Detection ◽  
Image Edge ◽  
Directional Wavelet

The information of the image edge is the important parameters in identifying, segmenting and compressing image. The performance of the algorithms about edge image algorithms closely relies on the noises generally included in the image. The main goal of this paper is firstly to eliminate the false edges by the median filter and extract the information of the edge image by directional wavelet transform. Application on image data shows that the proposed tool can enhance the direction edge images which is fused to form the complete image edge.

Insulator Image Denoising Based on the Simplified PCNN Model

2013 ◽  
Vol 718-720 ◽  
pp. 2092-2098 ◽  
Author(s):  
Dan Li ◽  
Hong Ying He ◽  
Yi Jia Cao ◽  
Dian Sheng Luo
Keyword(s):  
Impulse Noise ◽  
Signal To Noise Ratio ◽  
Median Filter ◽  
Infrared Image ◽  
Window Size ◽  
Denoising Method ◽  
Similarity Calculation ◽  
Image Edge ◽  
Filter Noise ◽  
Better Than

A new denoising method was proposed in the paper according to the characteristics of insulator infrared image with impulse noise. First, based on the pulse coupled neural network (PCNN) to detect the location of the impulse noise pixels, while maintaining the same non-noise pixels. and then according to the characteristics of the impulse noise, the window size of the filter was adaptively determined by calculating the noise intensity of the image. The pixels with maximum and minimum gray value in filtering window are excluded, using the left pixels similarity calculation out weights. A new weighted filtering algorithm is used to filter noise pixels. The experiments show that the method is better than the median filter in peak signal-to-noise ratio (PSNR), and has better image edge details protection ability.

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