Real-time segmentation of strawberry flesh and calyx from images of singulated strawberries during postharvest processing

- An image processing to extract the flesh and the calyx from an image is proposed.
- It relies on image color segmentation in a two dimensional color space.
- Results are improved thanks to a blob detection and selection stage.
- The algorithm is to tune and allows accurate extraction of the areas of interest.
- It deals with natural variation in strawberry shape and visual appearance.

This paper presents an image processing algorithm that automatically extracts the flesh and calyx areas from strawberry images. Images are captured by a camera included in a strawberry de-capping machine. Lighting is controlled and the background is known, conditions that are typical of postharvest processing. The goal is to extract as many flesh and calyx pixels as possible while rejecting any pixels belonging to the background. The proposed approach relies on image color segmentation in a two-dimensional color space, followed by a blob detection and selection stage. A set of 250 images is used to analyze the sensitivity of the algorithm with respect to user-defined parameters, and evaluate the performance of the approach. The algorithm appears to be easy to tune and allows accurate extraction of the areas of interest despite natural variation in strawberry shape and visual appearance. More than 98% of the flesh area was successfully extracted by the algorithm with less than 1% of the background pixels falsely included. Moreover, up to 79% of the calyx area could be extracted with less than 0.25% erroneous background pixels. Finally, the algorithm has been implemented using the C++ and Cuda languages and can be executed in real-time.