2013 ASABE Annual International Meeting Paper Page 1 An ASABE Meeting Presentation Paper Number: 1591603 Detecting and counting citrus fruit on the ground using machine vision Daeun Choi, Won Suk Lee, Reza Ehsani Agricultural and Biological Engineering Department, University of Florida, Gainesville, FL Written for presentation at the 2013 ASABE Annual International Meeting Sponsored by ASABE Kansas City, Missouri July 21 – 24, 2013 Abstract. A machine vision system for estimating number of citrus fruit drop was developed in this study. The objectives of this study were to design rugged hardware, to develop an image processing algorithm for accurate estimation of fruit count and to conduct field experiments. Image acquisition hardware was developed to be used in a commercial citrus grove specifically for unfavorable imaging conditions. The image processing algorithm included normalization of intensity, citrus fruit detection by a logistic classifier, and least square circle fitting. Accuracy of the algorithm was analyzed using two different methods. Firstly, the ability of detecting citrus fruit by the algorithm without any missed fruit was analyzed. The accuracy varied within three trials, and the highest was 89.5 percent. The second analysis was for the ability to avoid false positives which represent incorrect detection of the background object as a citrus. The percentage of false positive detection also varied between the trials. The highest error was 16.2 percent and the lowest error was 9.8 percent. Result of the experiments showed that each trial had different number and mass of citrus fruit drop. This was because each area in the images had different site-specific variable factors such as nutrient level, soil pH, disease, canopy size etc. The machine vision algorithm can be modified for more advanced application such as immature citrus fruit drop detection and counting during mechanical harvesting and early yield estimation. Keywords. Citrus fruit drop, CMNP, HLB Introduction Huanglongbing (HLB) is considered one of main reasons of early citrus fruit drop. Consequently the disease has resulted in a loss of yield. According to the Citrus forecast (United States Department of Agriculture - National Agricultural Statistics Services, 2012, 2013), there was a 9 percent production drop in non-Valencia and an 11 percent drop in Valencia for a total loss of 10 percent. To estimate an impact and loss resulting from HLB, accurate estimation of the amount of fruit drop is most important. Once the accurate estimation of the fruit The authors are solely responsible for the content of this meeting presentation. The presentation does not necessarily reflect the official position of the American Society of Agricultural and Biological Engineers (ASABE), and its printing and distribution does not constitute an endorsement of views which may be expressed. Meeting presentations are not subject to the formal peer review process by ASABE editorial committees; therefore, they are not to be presented as refereed publications. Citation of this work should state that it is from an ASABE meeting paper. EXAMPLE: Author's Last Name, Initials. 2013. Title of Presentation. ASABE Paper No. ---. St. Joseph, Mich.: ASABE. For information about securing permission to reprint or reproduce a meeting presentation, please contact ASABE at rutter@asabe.org or 269-932-7004 (2950 Niles Road, St. Joseph, MI 49085-9659 USA).