{"title":"基于大数据技术的数字图像处理和机器学习技术在地表卫星图像中的目标识别","authors":"Misba Khan k","doi":"10.46632/daai/3/2/27","DOIUrl":null,"url":null,"abstract":"Detection of an object from a satellite image is a difficult process because the presence of objects in a satellite image is unpredictable. Different approaches have been available to detect vehicles, buildings, trees however all these objects were detected individually through machine learning and some other methods. Similarly accuracy in object detection is another major issue. In our proposed work, To analyze the object accurately, Polygon approach is implemented which includes both shape and color as input and processes it with datasets to attain maximum accurate result. Here image parameters have been extracted accurately through feature detection. After segmentation of a particular object from image CNN classification is implemented. Through this, in our proposal we are going to detect roads, trees, buildings, waterway and few other objects accurately with this single approach.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Object Recognition in Earth Surface Satellite Images Using Digital Image Processing and Machine Learning Techniques with Big Data Technologies\",\"authors\":\"Misba Khan k\",\"doi\":\"10.46632/daai/3/2/27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Detection of an object from a satellite image is a difficult process because the presence of objects in a satellite image is unpredictable. Different approaches have been available to detect vehicles, buildings, trees however all these objects were detected individually through machine learning and some other methods. Similarly accuracy in object detection is another major issue. In our proposed work, To analyze the object accurately, Polygon approach is implemented which includes both shape and color as input and processes it with datasets to attain maximum accurate result. Here image parameters have been extracted accurately through feature detection. After segmentation of a particular object from image CNN classification is implemented. Through this, in our proposal we are going to detect roads, trees, buildings, waterway and few other objects accurately with this single approach.\",\"PeriodicalId\":226827,\"journal\":{\"name\":\"Data Analytics and Artificial Intelligence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data Analytics and Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46632/daai/3/2/27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data Analytics and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46632/daai/3/2/27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Object Recognition in Earth Surface Satellite Images Using Digital Image Processing and Machine Learning Techniques with Big Data Technologies
Detection of an object from a satellite image is a difficult process because the presence of objects in a satellite image is unpredictable. Different approaches have been available to detect vehicles, buildings, trees however all these objects were detected individually through machine learning and some other methods. Similarly accuracy in object detection is another major issue. In our proposed work, To analyze the object accurately, Polygon approach is implemented which includes both shape and color as input and processes it with datasets to attain maximum accurate result. Here image parameters have been extracted accurately through feature detection. After segmentation of a particular object from image CNN classification is implemented. Through this, in our proposal we are going to detect roads, trees, buildings, waterway and few other objects accurately with this single approach.