The invention discloses a
lotus seedpod target image recognition method for a picking
robot. The method includes the steps of designing a super green
Gaussian filter through the method that image
Gaussian filtering and the super green
index method are combined, and removing the complex background; separating and
cutting the overlapped portion of an image with the overlapping phenomenon through the improved morphology
watershed segmentation
algorithm; improving the Hu invariant moment
algorithm, calculating invariant moments an of
lotus seedpods,
lotus leaves, lotuses and stems, conducting linear combination on the calculated n orders of invariant moments, and obtaining invariant moment principle components zm representing different shape characteristics of the lotus seedpods, the lotus leaves, the lotuses and the stems; conducting image target recognition, wherein the invariant moment principle components zm of images of the lotus seedpods, the lotus leaves, the lotuses and the stems are classified through the K-Means clustering
algorithm. The connected components, closest to the lotus seedpod clustering center, of the principle components are the lotus seedpods. By means of the method, the lotus seedpods, the lotus leaves, the lotuses and the stems can be effectively distinguished and recognized, and the method is the core algorithm technology of a vision
system of the lotus seedpod picking
robot.