首页> 外文会议>International Conference on Frontiers of Intelligent Computing : Theory and Applications >A Real Time Fast Non-soft Computing Approach towards Leaf Identification
【24h】

A Real Time Fast Non-soft Computing Approach towards Leaf Identification

机译:一种实时快速非软计算方法叶鉴定

获取原文

摘要

In an agricultural country like India, majority of population depend on plant produce for their survival. Plants occupy a large portion of our ecosystem. In order to derive different benefits from plants in an optimum manner,one needs to be aware of the properties being possessed by plants. For that purpose,one needs to have proper source carrying significant information about plants and an expert so as to respond to ones queries. However, both these are not available in adequate which drives the need to create automation in the process of recognition of leaves for plant classification. Thus, a novel algorithm has been developed which helps in recognizing different varieties of leaves without human interference. The system uses real time images of leaves and extracts physiological as well as morphological features of the leaves, which are then fed as input to a classifier. The same has been implemented on a Back propagation based neural network classifier and a comparative study has been made. The study shows that the recognition rates of the proposed method are more accurate than that of BPNN and the proposed algorithm is found to be an efficient one.
机译:在像印度这样的农业国家,大多数人口依赖于植物产生的生存。植物占据了我们的大部分生态系统。为了以最佳的方式从植物中获得不同的益处,需要了解植物所拥有的属性。为此目的,人们需要具有适当的来源,携带有关植物和专家的重要信息,以便回应查询。然而,这两种都无法充分提供,这使得在植物分类的叶子的识别过程中需要创造自动化的必要性。因此,已经开发了一种新的算法,其有助于识别不同品种的叶片而没有人为干扰。该系统使用叶子的实时图像,提取生理学以及叶子的形态学特征,然后将其作为输入作为输入。已经在基于后传播的神经网络分类器上实现了相同的是,已经进行了比较研究。该研究表明,所提出的方法的识别率比BPNN的识别率更准确,并且发现所提出的算法是有效的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号