It is still a challenge for fruit robot to automatic detecting young green apples in a complex grove environment due to color similarity with the background and varying illumination conditions. The purpose of this study was developing a robust method to detect young green apples in the tree canopy from low-cost color images acquired with diverse fruit sizes and under varying light circumstances. Adaptive green and blue chromatic aberration map was designed and combined with the iterative threshold segmentation algorithm to detect the region of interest contains potential apple fruits pixels. Then every potential fruit was identified by using an improved circular Hough transformation after morphological operation and blob analysis of the ITS outs which kept as many potential apple fruits pixels as possible. Finally, a kernel support vector machine classifier optimized by using grid search algorithm was built and combined with histogram of oriented gradients feature descriptor to distinguish and remove false fruit objects. The experimental result shows that the proposed method has better detection performance for young green apples.
The precise management of orchards cannot do without the support of various orchard field data, and the orchard field data server is an effective solution thereto. The orchard field data server consists of data acquisition unit, data communication unit, data analysis unit and such diversified server sockets of user terminal as supportive personal computer (PC), notebook computer, mobile phone and telephone. The orchard workers can set data acquisition cycle according to the requirements, and the processed data can serve the orchard workers in many respects. After its promotion and application in many orchards in such regions as Liaoning and Beijing, the said system has been proved to be of easy use and reliable effect, so that the project has achieved good social, ecological and economic benefits.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.