Industry Track: An Image Classification and Browsing System for Farm Inspection

Masaki Ishihara, Shugo Nakamura, Takayuki Baba, Masahiko Sugimura, S. Endo, Y. Uehara, D. Masumoto
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引用次数: 2

Abstract

When a farmer shares information about farm situation or events with other farmers, he often uses pictures (images) taken during farm inspection for visual communication. However, it may take much time for the farmers to find the desired images from a large amount of images accumulated every day. Furthermore, the contents of the images are diverse (e.g. crop images, soil images, and field images), and the content of the desired images are dependent on the usage scene. Therefore, we develop an image classification and browsing system to suitable for the usage scene. We adopt a typical SVM image classification method using color histogram or layout of brightness as image features. The effectiveness of our system is verified by feasibility study in checking the growth situation of crops. The contribution of this work is the first attempt to apply the image classification and browsing technique to the farm inspection support in agricultural fields.
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行业专题:一种用于农场检验的图像分类和浏览系统
当农民与其他农民分享农场情况或事件的信息时,他经常使用在农场检查期间拍摄的照片(图像)进行视觉交流。然而,对于农民来说,从每天积累的大量图像中找到想要的图像可能需要花费很多时间。此外,图像的内容是多样的(例如,作物图像、土壤图像和田地图像),所需图像的内容依赖于使用场景。因此,我们开发了一个适合使用场景的图像分类浏览系统。我们采用一种典型的SVM图像分类方法,将颜色直方图或亮度布局作为图像特征。通过对作物生长状况的可行性研究,验证了该系统的有效性。本工作的贡献是首次尝试将图像分类和浏览技术应用于农业领域的农场检查支持。
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