{"title":"Leaf recognition based on artificial neural network","authors":"Furkan Ayaz, A. Ari, D. Hanbay","doi":"10.1109/IDAP.2017.8090240","DOIUrl":null,"url":null,"abstract":"Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After than filtered each image was scanned by 2×2 overlapping filter and maximum values of each shifting step was recorded. The dimension of each image reduced to it' half. Histogram of these uniform patterns were evaluated. These features were applied as input to the Artificial Neural Network (ANN) and 7 types of apricot were classified with the accuracy is 98.6 %.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAP.2017.8090240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Plant recognition from their leaves has become a popular area in the machine learning and image processing. In this study 7 different types of apricot trees were determined and classified by using their leaves. At first leaves images were pre-processed. After than each image was scanned by 5×5 overlapping filter and median values of each filter process were recorded to represent the leaves. After than filtered each image was scanned by 2×2 overlapping filter and maximum values of each shifting step was recorded. The dimension of each image reduced to it' half. Histogram of these uniform patterns were evaluated. These features were applied as input to the Artificial Neural Network (ANN) and 7 types of apricot were classified with the accuracy is 98.6 %.