Georjean D. S. Brown, C. Latonio, Richard Dean N. Oanes, Katrina R. Valentin, Edwin Jonathan F. Zara, Kanny Krizzy D. Serrano, E. Guevara, Angelo R. dela Cruz, A. Bandala, R. R. Vicerra
{"title":"利用热和视觉信息检测老鼠的机器视觉","authors":"Georjean D. S. Brown, C. Latonio, Richard Dean N. Oanes, Katrina R. Valentin, Edwin Jonathan F. Zara, Kanny Krizzy D. Serrano, E. Guevara, Angelo R. dela Cruz, A. Bandala, R. R. Vicerra","doi":"10.1109/HNICEM.2017.8269527","DOIUrl":null,"url":null,"abstract":"Pests, particularly rodents, are a major cause of problem to people because of the deadly diseases it spreads and the damage it does on field crops as it decreases billion worth of yield crop production in the Philippines. A detection measure to help eradicate rats is proposed by the researchers to prevent future failures or deficiencies in crop cultivation. Researchers developed a solution to this by designing and developing a Machine Vision System using thermal and visual identification for rodent identification. Thermal imaging uses infrared imaging to detect and record only thermal temperature patterns emitted by an object whereas visual imaging record videos exposed to good lighting and has not been configured for dark environment tracking. The rat detection accuracy of both individual cameras were recorded for data comparison and researchers proved that the use of a thermal camera arise to results that are more accurate than with the use of a visual camera.","PeriodicalId":104407,"journal":{"name":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Machine vision for rat detection using thermal and visual information\",\"authors\":\"Georjean D. S. Brown, C. Latonio, Richard Dean N. Oanes, Katrina R. Valentin, Edwin Jonathan F. Zara, Kanny Krizzy D. Serrano, E. Guevara, Angelo R. dela Cruz, A. Bandala, R. R. Vicerra\",\"doi\":\"10.1109/HNICEM.2017.8269527\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Pests, particularly rodents, are a major cause of problem to people because of the deadly diseases it spreads and the damage it does on field crops as it decreases billion worth of yield crop production in the Philippines. A detection measure to help eradicate rats is proposed by the researchers to prevent future failures or deficiencies in crop cultivation. Researchers developed a solution to this by designing and developing a Machine Vision System using thermal and visual identification for rodent identification. Thermal imaging uses infrared imaging to detect and record only thermal temperature patterns emitted by an object whereas visual imaging record videos exposed to good lighting and has not been configured for dark environment tracking. The rat detection accuracy of both individual cameras were recorded for data comparison and researchers proved that the use of a thermal camera arise to results that are more accurate than with the use of a visual camera.\",\"PeriodicalId\":104407,\"journal\":{\"name\":\"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HNICEM.2017.8269527\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM.2017.8269527","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine vision for rat detection using thermal and visual information
Pests, particularly rodents, are a major cause of problem to people because of the deadly diseases it spreads and the damage it does on field crops as it decreases billion worth of yield crop production in the Philippines. A detection measure to help eradicate rats is proposed by the researchers to prevent future failures or deficiencies in crop cultivation. Researchers developed a solution to this by designing and developing a Machine Vision System using thermal and visual identification for rodent identification. Thermal imaging uses infrared imaging to detect and record only thermal temperature patterns emitted by an object whereas visual imaging record videos exposed to good lighting and has not been configured for dark environment tracking. The rat detection accuracy of both individual cameras were recorded for data comparison and researchers proved that the use of a thermal camera arise to results that are more accurate than with the use of a visual camera.