Multi-scale image segmentation of coal piles on a belt based on the Hessian matrix

• A new image segmentation algorithm for coal piles on belt was proposed.
• A multi-scale linear filter was constructed of Hessian matrix and Gaussian function.
• Good seed regions for watershed segmentation were obtained by a series of sub-algorithms.
• Verification showed that the new algorithm is feasible and effective in practical applications.

Segmenting images of coal piles on a belt is an unsolved problem in coal-based machine vision research, though it is an essential step for estimating size distribution and classifying coal. In this investigation, a new algorithm for segmenting images of coal piles on a belt is proposed. A multi-scale linear filter, constructed of a Hessian matrix and Gaussian function, forms the core of this algorithm and obtains an edge intensity image to form good seed regions for a watershed segmentation. Manual segmentation is used to define ground truth segmentation images to quantify the errors of the proposed method. Tests indicate that 12.76% of the visible regions are under- or over-segmented, and that this algorithm is feasible and effective in practical applications.

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