A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Authenticating Edges Produced by Zero-Crossing Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Visual Method for Assessing the Relative Performance of Edge-Detection Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Local Scale Control for Edge Detection and Blur Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computers & Geosciences - Special issue on system integration within the geosciences
Computation reduction for motion search in low rate video coders
IEEE Transactions on Circuits and Systems for Video Technology
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To quickly and accurately estimate average size of densely packed particles on a fast moving conveyor belt, a new image processing method is designed and studied. The method consists of two major algorithms, one is a one-pass boundary detection algorithm that is specially designed for the images of densely packed particles (the word “particle” is used in a wide sense), and the other is average size estimation based on image edge density. The algorithms are cooperative. The method has been tested experimentally for different kinds of closely packed particle images which are difficult to detect by ordinary image segmentation algorithms. The new method avoids delineating and measuring every particle on an image, therefore, is suitable for real-time imaging. It is particularly applicable for a densely packed and complicated particle image sequence.