{"title":"图像处理和神经网络在确定玉米成熟状态中的应用","authors":"A. Peter, S. Abdulkadir","doi":"10.1145/3184066.3184068","DOIUrl":null,"url":null,"abstract":"1. Amongst crops cultivated in Nigeria, maize tends to rank the highest due to its nutrient contents of carbohydrate, fat and protein. The entire maize plant is a good source of food for livestock. Nevertheless, the plant is left to attain biological maturity in Nigeria where the leaves have little or no nutritional content. Before biological maturity, the maize kernel is ready for harvest and the maize plant is still having its green coloration. Changes in the maize plant were studied before physiological maturity, at physiological maturity and before biological maturity. Images of the three stages mentioned were obtained using a charge coupled device (CCD) camera. Significant color features were extracted and used as inputs in determining the classification by neural network. The network achieved an accuracy of 100% based on the sample set.","PeriodicalId":109559,"journal":{"name":"International Conference on Machine Learning and Soft Computing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Application of image processing and neural networks in determining the readiness of maize\",\"authors\":\"A. Peter, S. Abdulkadir\",\"doi\":\"10.1145/3184066.3184068\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"1. Amongst crops cultivated in Nigeria, maize tends to rank the highest due to its nutrient contents of carbohydrate, fat and protein. The entire maize plant is a good source of food for livestock. Nevertheless, the plant is left to attain biological maturity in Nigeria where the leaves have little or no nutritional content. Before biological maturity, the maize kernel is ready for harvest and the maize plant is still having its green coloration. Changes in the maize plant were studied before physiological maturity, at physiological maturity and before biological maturity. Images of the three stages mentioned were obtained using a charge coupled device (CCD) camera. Significant color features were extracted and used as inputs in determining the classification by neural network. The network achieved an accuracy of 100% based on the sample set.\",\"PeriodicalId\":109559,\"journal\":{\"name\":\"International Conference on Machine Learning and Soft Computing\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Machine Learning and Soft Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3184066.3184068\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Machine Learning and Soft Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3184066.3184068","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of image processing and neural networks in determining the readiness of maize
1. Amongst crops cultivated in Nigeria, maize tends to rank the highest due to its nutrient contents of carbohydrate, fat and protein. The entire maize plant is a good source of food for livestock. Nevertheless, the plant is left to attain biological maturity in Nigeria where the leaves have little or no nutritional content. Before biological maturity, the maize kernel is ready for harvest and the maize plant is still having its green coloration. Changes in the maize plant were studied before physiological maturity, at physiological maturity and before biological maturity. Images of the three stages mentioned were obtained using a charge coupled device (CCD) camera. Significant color features were extracted and used as inputs in determining the classification by neural network. The network achieved an accuracy of 100% based on the sample set.