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  • 标题:Variance Analysis Based Mango Recognition Using Correlation Distance
  • 本地全文:下载
  • 作者:Farhana Tazmim Pinki ; S.M. Mohidul Islam
  • 期刊名称:International Journal of Image, Graphics and Signal Processing
  • 印刷版ISSN:2074-9074
  • 电子版ISSN:2074-9082
  • 出版年度:2020
  • 卷号:12
  • 期号:5
  • 页码:37-43
  • DOI:10.5815/ijigsp.2020.05.04
  • 出版社:MECS Publisher
  • 摘要:Mango plays a major role in the Agro industry and it is a very popular fruit to most of the people due to its flavor and taste. There are many varieties of mangoes that are differentiable based on their various characteristics. Sometimes it is difficult and time consuming for general people or farmers to categorize the mango into different types due to intra-class variation among various types of mangoes. This paper has proposed an automatic system to recognize mangoes thus it becomes convenient to identify various types of mangoes. In this method, mangoes are recognized into different categories based on variance analysis or data dispersion measures. Measures include five number summary, variance, mean deviation, skewness, coefficient of variation which are used as features. From both training and query images, feature vectors are created. Correlation is used to recognize mangoes into various categories. The proposed method shows better result than some existing methods.
  • 关键词:Image Processing; Variance; Correlation; Feature Vector; Mango Recognition;
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