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- W2063373241 abstract "Froth image segmentation is an important and basic part in an online froth monitoring system in mineral processing. The fast and accurate bubble delineation in a froth image is significant for the subsequent froth surface characterization. This paper proposes a froth image segmentation method combining image classification and image segmentation. In the method, an improved Harris corner detection algorithm is applied to classify froth images first. Then, for each class, the images are segmented by automatically choosing the corresponding parameters for identifying bubble edge points through extracting the local gray value minima. Finally, on the basis of the edge points, the bubbles are delineated by using a number of post-processing functions. Compared with the widely used Watershed algorithm and others for a number of lead zinc froth images in a flotation plant, the new method (algorithm) can alleviate the over-segmentation problem effectively. The experimental results show that the new method can produce good bubble delineation results automatically. In addition, its processing speed can also meet the online measurement requirements." @default.
- W2063373241 created "2016-06-24" @default.
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- W2063373241 date "2015-03-30" @default.
- W2063373241 modified "2023-10-02" @default.
- W2063373241 title "Flotation Bubble Delineation Based on Harris Corner Detection and Local Gray Value Minima" @default.
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- W2063373241 doi "https://doi.org/10.3390/min5020142" @default.
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