C. Yensiri, C. Seetao, Pomwilai Sukmak, M. Lohakan
{"title":"A Training Set of Digital Image Processing for Object Inspection using Lab VIEW","authors":"C. Yensiri, C. Seetao, Pomwilai Sukmak, M. Lohakan","doi":"10.1109/RI2C51727.2021.9559832","DOIUrl":null,"url":null,"abstract":"This research proposes a training set of digital image processing using LabVIEW for object inspection topic. The collection consists of a conveyor set, digital camera, a robot arm, a training book, and 12 VDO clips. The conveyor base and frame are elaborately created by a 3D printer with PLA plastic. The conveyor which rotates circularly is driven by a dc motor. It is graphically controlled by LabVIEW, which interfaces with a microcontroller board and dc motor. A robot arm operates as a rejecting arm, pushing an unwanted object away from the conveyor. The inspection process employs a real-time USB camera and infrared light sensors incorporating a digital image processing algorithm. Additionally, the training book comprises of 12 chapters which match with 12 VDO clips combined as a learning set. A batch of VDO clips is published online through the YouTube channel. Content examples are color detection, object shape classification, motor control, reject arm control, and water level inspection. Details of each chapter are apparatus preparation, the graphically programming process, and GUI design. The 12 VDO clips are also added to the training package for self-study. A compact size and easiness to replicate and carry of conveyor set are the advantages of the training set. The training package was evaluated by 6 expert lecturers from the department of Teacher Training in Electrical Engineering, KMUTNB, with an average value of 4.30 from 5. The training set also is assessed by 26 students from the senior class. Finally, the evaluated results show that the training set can improve student's enthusiasm, and easy understanding and serve as encouragement.","PeriodicalId":422981,"journal":{"name":"2021 Research, Invention, and Innovation Congress: Innovation Electricals and Electronics (RI2C)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Research, Invention, and Innovation Congress: Innovation Electricals and Electronics (RI2C)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RI2C51727.2021.9559832","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This research proposes a training set of digital image processing using LabVIEW for object inspection topic. The collection consists of a conveyor set, digital camera, a robot arm, a training book, and 12 VDO clips. The conveyor base and frame are elaborately created by a 3D printer with PLA plastic. The conveyor which rotates circularly is driven by a dc motor. It is graphically controlled by LabVIEW, which interfaces with a microcontroller board and dc motor. A robot arm operates as a rejecting arm, pushing an unwanted object away from the conveyor. The inspection process employs a real-time USB camera and infrared light sensors incorporating a digital image processing algorithm. Additionally, the training book comprises of 12 chapters which match with 12 VDO clips combined as a learning set. A batch of VDO clips is published online through the YouTube channel. Content examples are color detection, object shape classification, motor control, reject arm control, and water level inspection. Details of each chapter are apparatus preparation, the graphically programming process, and GUI design. The 12 VDO clips are also added to the training package for self-study. A compact size and easiness to replicate and carry of conveyor set are the advantages of the training set. The training package was evaluated by 6 expert lecturers from the department of Teacher Training in Electrical Engineering, KMUTNB, with an average value of 4.30 from 5. The training set also is assessed by 26 students from the senior class. Finally, the evaluated results show that the training set can improve student's enthusiasm, and easy understanding and serve as encouragement.