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A binocular camera composed of colour and depth cameras is an accurate and inexpensive tool for recognising fruit trees to plan spraying paths. For this purpose, however, the accurate visual registration of the depth and colour cameras is a problem that must be solved. This paper proposes a local feature point extraction (LFPE) algorithm for depth-colour image registration, which automatically extracts the feature points of local regions in the colour and depth images for registration. First, the binarised colour and depth images are divided into local regions after edge extraction, and the regions in which the edge features match at several pixels between images are selected. Then, these regions are again divided into smaller regions to detect local extrema of the pixels as feature points. Finally, the matching feature points are calculated based on the Euclidean distance and are used to optimise the affine transformation matrix. To verify the accuracy and effectiveness of the algorithm, it is compared with the FAST, SURF and BRISK algorithms. The experimental results show that the accuracy of the proposed LFPE algorithm is 1.6 times that of BRISK, 3.5 times that of FAST and 40.1 times that of SURF. Therefore, it is more suitable for registration between depth and colour images. • Proposed a depth-colour image registration method for orchard precision spraying. • A local feature point extraction (LFPE) algorithm is proposed to match images. • The registration accuracy of LFPE is much better than other similar algorithms. [ABSTRACT FROM AUTHOR]