Immature citrus fruit detection based on local binary pattern feature and hierarchical contour analysis

摘要

Detecting immature fruit in groves provides a promising benefit for growers to plan application of nutrients and estimate their yield and profit prior to harvesting. The goal of this study was to develop a robust algorithm to detect and count immature citrus fruit in images of the tree canopy. Images were all taken in low natural light conditions with a flashlight, and the green component of the colour images was used for further analysis. Local intensity maxima were detected and local binary pattern (LBP) features around them were extracted as an input of an ensemble classifier-RUSBoost. The positive predictions were considered as candidates and the hierarchical contour maps around them were extracted and fitted with Circular Hough Transform. The fitted circles were predicted as fruit targets if its radius were in a predetermined range.