NDLI: Sand grains tracking in dense grain image sequences

Content Provider	IEEE Xplore Digital Library
Author	Chunli Wang Dapeng Chai Rui Ma Xiaohui Lin Chun Wang
Copyright Year	2008
Description	Author affiliation: Sch. of Inf. Sci. & Technol., Dalian Maritime Univ., Dalian (Chunli Wang)
Abstract	In experiments of soil mechanics, it is important to study the motion of sand grains at high pressures. Technologies of image segmentation and object tracking can help to resolve this problem. Aiming at the dense sand grains images, this paper proposes a method to track sand grains from image sequences. A novel approach of dense grain segmentation based on boundary exploration is proposed. Firstly, adaptive Canny is employed to detect edges. Mathematical Morphologic methods are utilized to eliminate the noises. Secondly, seeds are chosen based on the histogram in each sub-image. And then rays are emitted from each seed to explore the boundary. The false boundary points are identified using an estimation strategy and modified automatically. After the contours of grains are achieved, the detected sand regions are tracked based on Multi-Feature Multi-Layer matching. Several experiments are performed. Promising segmentation and tracking results can be obtained on dense grain images.
Starting Page	344
Ending Page	349
File Size	384581
Page Count	6
File Format	PDF
ISBN	9781424423576
DOI	10.1109/CIT.2008.4594699
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-07-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image edge detection Noise Clustering algorithms Distance measurement Classification algorithms Pixel
Content Type	Text
Resource Type	Article

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