Recognition of Leaves in Videos

M. Naveena, Vidyashankara, G. Kumar
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Abstract

The aim of this paper work is to design a user independent framework for recognizing and classifying the leaves in a video frames. This project involves classification of leaves using KNN (K- Nearest Neighbor) as a classifier. SURF (Speeded-Up Robust Features) and LBP (Local Binary Pattern) features are used for extracting Scale ,Orientation etc., In the first step our proposed model can extract most distinguish key-frames and then from extracted key-frames it detects the leaf color and recognize the different class of leaves.
视频中叶子的识别
本文的目的是设计一个独立于用户的框架来识别和分类视频帧中的叶子。这个项目涉及使用KNN (K-最近邻)作为分类器对叶子进行分类。利用SURF(加速鲁棒特征)和LBP(局部二值模式)特征提取尺度、方向等特征,首先提取出大部分可区分的关键帧,然后从提取的关键帧中检测出叶子的颜色并识别出不同类别的叶子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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