A registration algorithm for the infrared and visible images of apple based on active contour model

To study the fruit image fusion technology in the case of thermal infrared and visible heterogeneous sources and the method of online defect detection on fruit fusion images, this paper takes apple as the research object and proposes a registration algorithm for thermal infrared and visible images of apple based on the registration of feature points with an active contour model. First, by designing a thermal infrared and visible image acquisition system, thermal infrared and visible images of apple in the same scene are obtained simultaneously. Then, the improved Chan-vese model is adopted to obtain the active contour segmentation curves of the thermal infrared and visible images of apple respectively. Next, the average Euclidean distance of all adjacent edge points on the active contour segmentation curve is calculated, and the alignment feature point set is constructed by the linear interpolation method based on the obtained average distance, and the optimal scale transformation factor and the optimal horizontal transformation factor are obtained by calculating the partial Hausdorff distance between the two feature point sets. Finally, the registered visible image is acquired based on the obtained affine transformation matrix, thus realizing the registration of the thermal infrared and visible images of apple. The experimental results on the self-built image dataset indicate that the algorithm proposed in this paper can accurately match the heterogeneous images of intact fruit, calyx/stems, and defective fruit, and it performs excellently in terms of precise matching rate and root mean square error, and the high alignment success rate of 96