Random forest algorithm has the advantages of fast processing speed in image processing, and can be used in image segmentation. The aim of this paper is to study image segmentation based on random forests. The principles of random forest algorithm and feature extraction are described in detail, and the characteristics of RGB colour space and HSV colour space are analysed. The experimental procedure for segmenting annual rings images is described. Regions of interest are extracted and then, based on the differences in colour and texture features of early and late wood, the segmentation of annual rings images is achieved. The experimental results show that the random forest algorithm achieves better results in image segmentation.

Weiwei Gao. Random Forest in Image Segmentation. Machine Learning Theory and Practice (2020), Vol. 1, Issue 3: 11-19. https://doi.org/10.38007/ML.2020.010302.

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