A new approach to combining region growing and edge detection

1993 ◽  
Vol 14 (11) ◽  
pp. 869-875 ◽  
Author(s):  
Jean-Pierre Gambotto
Keyword(s):  
Edge Detection ◽  
Region Growing ◽  
New Approach

scholarly journals A Multi-Focus Image Fusion Algorithm Based on Contrast Pyramids

2016 ◽  
Author(s):  
Mingzhu Lai ◽  
Jianguo Sun ◽  
Liguo Zhang ◽  
Yiran Shen ◽  
Qing Yang ◽  
...  
Keyword(s):  
Image Fusion ◽  
Region Growing ◽  
Fusion Algorithm ◽  
New Approach ◽  
Focus Image ◽  
Focus Information ◽  
Robust To Noise

This paper proposes a new approach for multi-focus images fusion based on Region Mosaicing on Contrast Pyramids (REMCP). A density-based region growing method is developed to construct a focused region mask for multi-focus images. The segmented focused region mask is decomposed into a mask pyramid, which is then used for supervised region mosaicking on a contrast pyramid. In this way, the focus measurement and the continuity of focused regions are incorporated and the pixel level pyramid fusion is improved at the region level. Objective and subjective experiments show that the proposed REMCP is more robust to noise than compared algorithms and can fully preserves the focus information of the multi-focus images meanwhile reducing distortions of the fused images.

A new approach to image segmentation based on simplified region growing PCNN

2008 ◽  
Vol 205 (2) ◽  
pp. 807-814 ◽  
Author(s):  
Yunfeng Lu ◽  
Jun Miao ◽  
Lijuan Duan ◽  
Yuanhua Qiao ◽  
Ruixin Jia
Keyword(s):  
Image Segmentation ◽  
Region Growing ◽  
New Approach

scholarly journals A Vision-Based Approach for Sidewalk and Walkway Trip Hazards Assessment

2020 ◽  
Vol 17 (22) ◽  
pp. 8438
Author(s):  
Rachel Cohen ◽  
Geoff Fernie ◽  
Atena Roshan Fekr
Keyword(s):  
Environmental Factors ◽  
Edge Detection ◽  
Gaussian Process ◽  
Regression Models ◽  
Gaussian Process Regression ◽  
Region Growing ◽  
Cost Effective ◽  
Second Phase ◽  
Cost Effective Method ◽  
Regression Techniques

Tripping hazards on the sidewalk cause many falls annually, and the inspection and repair of these hazards cost cities millions of dollars. Currently, there is not an efficient and cost-effective method to monitor the sidewalk to identify any possible tripping hazards. In this paper, a new portable device is proposed using an Intel RealSense D415 RGB-D camera to monitor the sidewalks, detect the hazards, and extract relevant features of the hazards. This paper first analyzes the effects of environmental factors contributing to the device’s error and compares different regression techniques to calibrate the camera. The Gaussian Process Regression models yielded the most accurate predictions with less than 0.09 mm Mean Absolute Errors (MAEs). In the second phase, a novel segmentation algorithm is proposed that combines the edge detection and region-growing techniques to detect the true tripping hazards. Different examples are provided to visualize the output results of the proposed method.

scholarly journals Goose eggshell geometry

2014 ◽  
Vol 60 (No. 3) ◽  
pp. 100-106 ◽  
Author(s):  
Š. NEDOMOVÁ ◽  
J. BUCHAR
Keyword(s):  
Fourier Series ◽  
Edge Detection ◽  
Surface Area ◽  
Digital Image ◽  
Radius Of Curvature ◽  
Egg Volume ◽  
New Approach ◽  
Detection Techniques ◽  
The Common

The paper presents a new approach of the eggshell geometry determination using and analysing the egg digital image and edge detection techniques. The detected points on the eggshell contour were fitted by the Fourier series. The obtained equations describing an egg profile were used to calculate the egg volume, surface area, and radius of curvature with much higher degree of precision in comparison with previously published approaches. The paper shows and quantifies the limitations of the common and frequent procedures.

Probabilistic segmentation using edge detection and region growing

1992 ◽  
Author(s):  
Russell R. Stringham ◽  
William A. Barrett ◽  
David C. Taylor
Keyword(s):  
Edge Detection ◽  
Region Growing
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