基于SVM分类器和决策树的鸟类物种识别

Baowen Qiao, Zuofeng Zhou, Hongtao Yang, Jianzhong Cao
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引用次数: 16

摘要

由于光照的变化和相机视角的不同,鸟类识别是一个具有挑战性的问题。本文利用眼睛到喙根的距离与喙宽距离的比值这一新的特征来区分不同的鸟类。将新特征融合到多尺度决策树和支持向量机框架中,提出了一种新的鸟类物种识别算法,得到最终的识别结果。实验结果表明,所提出的新特征可将分类正确率提高约9%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bird species recognition based on SVM classifier and decision tree
Bird species recognition is a challenging problem due to the variant illumination and different view point of camera. In this paper, a new feature which is the ratio between the distance of the eye to the root of beak and the distance of the width of the beak is used to distinguish the different bird species. Integrated the new feature into the multi-scale decision tree and the SVM framework, a new bird species recognition algorithm is proposed to get the final recognition result. The Experiment results show that the proposed new feature can improve the correct classification rate about nine percent.
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