Title :
Study on Crop Image Feature Extraction of Vehicle-Based Estimation System on Large Scale Crop Acreage
Author :
Wang, Su-xia ; Song, Zheng-he ; Zhu, Zhong-xiang ; Yang, Bang-jie ; Mao, En-rong ; Zhang, Rui
Author_Institution :
China Agric. Univ., Beijing
Abstract :
Vehicle-based estimation system on large scale crop acreage, which was equipped with GPS receivers, GIS software and a video camera on a off-road vehicle, can capture the images of video and calculate the crop acreage proportion based on matching between GPS information and image recognition. The system provides the credible data for government to make decision and provides technological method. In order to enhance the real-time and reliable character of the system, namely improve the precision of image recognition and estimation result, the grid algorithm of the crop image feature extraction was proposed. The principle of the grid algorithm was that the every crop image was segmented to 16 grids averagely and the four corner grids were regarded as the beginning area during feature extraction and crop recognition. Whether or not to continue extracting feature and recognizing in other grids as well as the recognizing sequence was determined according to the result of crop recognition in the four beginning areas. The texture feature, the shape feature and the color feature were extracted in terms of the particularity of the crop recognition, then the different features or the feature combination were used in order to recognize the crop. The detailed analysis methods of different crops and different cultivating condition were discussed in this paper.
Keywords :
Global Positioning System; agriculture; crops; feature extraction; image recognition; GIS software; GPS receivers; crop image feature extraction; image recognition; large scale crop acreage; off-road vehicle; vehicle-based estimation system; video camera; Cameras; Crops; Feature extraction; Geographic Information Systems; Global Positioning System; Government; Image recognition; Large-scale systems; Real time systems; Vehicles; Color feature; Feature extraction; Grid; Shape feature; Texture feature;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370173