Detection of grapes in natural environment using HOG features in low resolution images

[摘要] Detection of grapes in real-life images has importance in various viticulture applications. A grape detector based on an SVM classifier, in combination with a HOG descriptor, has proven to be very efficient in detection of white varieties in high-resolution images. Nevertheless, the high time complexity of such utilization was not suitable for its real-time applications, even when a detector of a simplified structure was used. Thus, we examined possibilities of the simplified version application on images of lower resolutions. For this purpose, we designed a method aimed at search for a detector's setting which gives the best time complexity vs. performance ratio. In order to provide precise evaluation results, we formed new extended datasets. We discovered that even applied on low-resolution images, the simplified detector, with an appropriate setting of all tuneable parameters, was competitive with other state of the art solutions. We concluded that the detector is qualified for real-time detection of grapes in real-life images.

[发布机构] Faculty of Electrical Engineering and Informatics, University of Pardubice, Studentská 95, Pardubice; 532 10, Czech Republic^1

[效力级别] 无线电电子学

[关键词] Evaluation results;High resolution image;Low resolution images;Natural environments;Performance ratio;Real-time application;Real-time detection;Tuneable parameters