Recognition and localization of actinidia arguta based on image recognition

Abstract

In the process of picking, actinidia arguta has difficulty in image recognition and occlusion problems, and there are few studies on kiwifruit recognition. Based on this, this study uses the color model to perform image basic processing and uses frequency domain enhancement to process the image. Simultaneously, in the frequency domain of the image, this study applied filtering to the original image of kiwifruit orchard, used homomorphic filtering to enhance the image of actinidia arguta orchard, highlighted the characteristics of actinidia arguta trunk, and reduced the influence of background noise on the recognition of actinidia arguta trunk. In addition, this study used a binocular stereo vision system for fruit location recognition to improve recognition accuracy. Finally, the effectiveness of the research method is verified by experimental research. The results show that the proposed algorithm performs well and can provide theoretical references for subsequent related research.