首页> 外文期刊>International Journal of Engineering and Technology >Medicinal Plant Recognition of Leaf Shape using Localized Arc Pattern Method
【24h】

Medicinal Plant Recognition of Leaf Shape using Localized Arc Pattern Method

机译:采用局部电弧模式法的药用植物识别

获取原文
           

摘要

Medicinal plants are plants that have benefit in order to supply the needs of familiestraditionally medicine. Medicinal plants have diverse types that causing modern society have difficulty inrecognizing these crops. Medicinal plants generally can be identified by the leaves, stems and fruit. One ofthe leaves characteristics can be distinguished based on vein structure and shape of its. Based on theseproblem, plant recognition based on vein and shape are made by using Localized Arc Pattern Method.There are two important processes in Plant Recognition Applications. First process is Enrollment andthe second is Recognition process. In the Enrolment process, the leaves image filed as many as 6 imagesfor each leaves type. This image then calculated based on the 42 special model pattern obtained and thefeature is stored as a reference image. Leaves images that used as test image are 200 images. On theRecognition process, the test image will be process which as same as at Enrollment process, howeverfeature from the test image will be comparing with reference image in database, then it calculate thedifference value. This process uses a threshold value to determine whether the test images leaves arerecognized or not. When dissimilarity value is smaller than the threshold is known as the same leaves,when instead then it known as a different leaves or not known at all. Experiment result shows in thisapplication can recognize 77% of total leaves and False Accepted Ratio (FAR) equal to 4.5% and FalseRejection Ratio (FRR) equal to 18.5%. This result was influenced by the shiny surface of leaf and shapeof the leaves are small.
机译:药用植物是有利于提供家庭医学需求的植物。药用植物具有多种类型的类型,导致现代社会难以抵押这些作物。药用植物通常可以通过叶,茎和果实鉴定。可以基于静脉结构和形状来区分叶子特征之一。基于这些问题,通过使用局部弧形模式法进行了基于静脉和形状的植物识别。工厂识别应用中有两个重要过程。第一个进程是注册,第二个是识别过程。在注册过程中,对于每种叶片类型,叶子图像提交多达6张图片。然后基于所获得的42个特殊模型模式计算该图像,并且将其存储为参考图像。留下用作测试图像的图像是200图像。在治疗过程中,测试图像将是与注册过程相同的过程,但是从测试图像中的Feature将与数据库中的参考图像进行比较,然后它计算附带的值。该过程使用阈值来确定测试图像是否落后令人未知。当相似值小于阈值时,被称为相同的叶子,然后何时被称为不同的叶子或根本不知道。实验结果表明在该应用中可以识别77%的总叶片和错误接受比率(远)等于4.5%,虹压比(FRR)等于18.5%。该结果受到叶片闪亮表面的影响,叶子的形状很小。

著录项

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