首页> 外文会议>International Conference on Informatics and Computing >Identification using the K -Means Clustering and Gray Level Co-occurance Matrix (GLCM) At Maturity Fruit Oil Head
【24h】

Identification using the K -Means Clustering and Gray Level Co-occurance Matrix (GLCM) At Maturity Fruit Oil Head

机译:在成熟果油头上使用K-MEANS聚类和灰度级共发矩阵(GLCM)识别

获取原文

摘要

This study discusses the identification of its palm fruit camp picture image using K-Means Clustering and identification GLCM. Process fruits traditionally experienced constrained due to human nature that has flaws that the desired results are not effective. Advances in computer technology have come into the world in terms of the farm before harvest and post-harvest. This Dimolished how to recognize the fruit so that it correspond to real conditions. Condition of oil palm fruit is determined by the level of maturity in terms of color, texture and shape of the oil palm fruit. Identification which did classify in the category of mature and not mature. Determination of identification with the K-means clustering method that uses the difference in euclidean distance and GLCM feature extraction as a reference. For the results of the present study is equal to 90% of the 50 test data.
机译:本研究讨论了使用K-Means聚类和识别GLCM识别其棕榈水果阵营图像图像。流程果实传统上由于人性而受到限制,这些人性具有缺陷所需的结果无效。计算机技术的进展在收获之前的农场进入世界,并收获后的农场。这使得如何识别果实使其对应于真实条件。油棕水果的状况由油棕榈果的颜色,质地和形状方面的成熟程度决定。在成熟的类别中进行分类,而不是成熟的识别。用k-means聚类方法确定使用欧几里德距离和GLCM特征提取的差异作为参考的识别方法。对于本研究的结果,等于50个测试数据的90%。

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