Title :
Detection Method for the Buds on Winter Vines Based on Computer Vision
Author :
Sheng Xu ; Yi Xun ; Tingmeng Jia ; Qinghua Yang
Author_Institution :
Mech. & Electr. Eng. Dept., Zhejiang Bus. Technol. Inst., Ningbo, China
Abstract :
According to the requirement of grape pruning in winter, an algorithm of detecting the buds of grape vines based on machine vision was proposed, laying the foundation of grape vines automotive pruning. The grapevines´ color image was captured indoor. The blue component of the color image was selected for the image preprocessing such as filter, threshold segmentation and noise removal. After that a binary image was gained. With the binary image, Rosenfeld algorithm was used in thinning to extract the skeleton of the grape branches. Because the morphological characteristic of the buds was similar to the corners, Harris algorithm was chosen to detect the point of buds from the skeleton image. The experiment result showed that it´s effective to detect the buds with the strategy of this paper. The recognition rate reached 70.2%.
Keywords :
agricultural products; computer vision; filtering theory; image colour analysis; image denoising; image segmentation; object detection; Rosenfeld algorithm; binary image; computer vision; filter; grape vine bud detection method; grape vine color image; grape vine pruning; image preprocessing; machine vision; noise removal; threshold segmentation; winter vines; Algorithm design and analysis; Correlation; Feature extraction; Histograms; Pipelines; Shape; Skeleton; Bud detection; Grapevine winter pruning; Harris algorithm; Machine vision; Rosenfeld algorithm;
Conference_Titel :
Computational Intelligence and Design (ISCID), 2014 Seventh International Symposium on
Print_ISBN :
978-1-4799-7004-9
DOI :
10.1109/ISCID.2014.26