Year-end Sale % OFF 
Abstract
For yield measurement of an apple orchard or the mechanical harvesting of apples, there needs to be accurate identification of the target apple fruit. However, in a natural scene, affected by the apple’s growth posture and camera position, there are many kinds of apple images, such as overlapped apples; mutual shadows or leaves; stems; etc. It is a challenge to accurately locate overlapped apples. They will influence the positioning time and recognition efficiency and then affect the harvesting efficiency of apple-harvesting robots or the accuracy of orchard yield measurement. In response to this problem, an overlapped circle positioning method based on local maxima is proposed. First, the apple image is transformed into the Lab color space and segmented by the K-means algorithm. Second, some morphological processes, like erosion and dilation, are implemented to abstract the outline of the apples. Then image points are divided into central points; edge points; or outer points. Third, a fast algorithm is used to calculate every internal point’s minimum distance from the edge. Then, the centers of the apples are obtained by finding the maxima among these distances. Last, the radii are acquired by figuring out the minimum distance between the center and the edge. Thus, positioning is achieved. Experimental results showed that this method can locate overlapped apples accurately and quickly when the apple contour was complete; and this has certain practicability.
Highlights
In the related research on apple orchards’ yield measurements or mechanical harvesting of apples [1,2,3], this is the key to recognizing and localizing apple targets
This paper presents a localization method of overlapped apples based on maxima
Apple contours were obtained after some morphological processing
Summary
In the related research on apple orchards’ yield measurements or mechanical harvesting of apples [1,2,3], this is the key to recognizing and localizing apple targets. For the identification and location of a target fruit, a lot of research has been carried out, and gratifying achievements have been made [4,5,6,7]. They are mainly devoted to the research of static or non-vibrating single shadow fruits. For overlapped apples, it is difficult to pinpoint them They will affect the localization and recognition accuracy, which in turn will affect the harvesting efficiency of the apple harvesting robot or the production accuracy of the orchard yield measurement
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
