{"title":"热成像中的行人分割","authors":"Karol Piniarski, P. Pawlowski","doi":"10.23919/URSI.2018.8406765","DOIUrl":null,"url":null,"abstract":"Image segmentation is one of crucial stages of video processing used for detection of pedestrians in infrared (IR) vision. The paper presents a study of passive (typically far IR) technologies for IR vision and an analysis of the state-of-the-art in the extraction of information from IR images. A deep testing of segmentation methods was performed for IR images with a specially prepared benchmark of 162 IR video frames with pedestrians. The initial tests included two segmentation methods: the single threshold and the Otsu method. The obtained results are promising as the effectiveness reaches ca. 82% for both techniques.","PeriodicalId":362184,"journal":{"name":"2018 Baltic URSI Symposium (URSI)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Segmentation of pedestrians in thermal imaging\",\"authors\":\"Karol Piniarski, P. Pawlowski\",\"doi\":\"10.23919/URSI.2018.8406765\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image segmentation is one of crucial stages of video processing used for detection of pedestrians in infrared (IR) vision. The paper presents a study of passive (typically far IR) technologies for IR vision and an analysis of the state-of-the-art in the extraction of information from IR images. A deep testing of segmentation methods was performed for IR images with a specially prepared benchmark of 162 IR video frames with pedestrians. The initial tests included two segmentation methods: the single threshold and the Otsu method. The obtained results are promising as the effectiveness reaches ca. 82% for both techniques.\",\"PeriodicalId\":362184,\"journal\":{\"name\":\"2018 Baltic URSI Symposium (URSI)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Baltic URSI Symposium (URSI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/URSI.2018.8406765\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Baltic URSI Symposium (URSI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/URSI.2018.8406765","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image segmentation is one of crucial stages of video processing used for detection of pedestrians in infrared (IR) vision. The paper presents a study of passive (typically far IR) technologies for IR vision and an analysis of the state-of-the-art in the extraction of information from IR images. A deep testing of segmentation methods was performed for IR images with a specially prepared benchmark of 162 IR video frames with pedestrians. The initial tests included two segmentation methods: the single threshold and the Otsu method. The obtained results are promising as the effectiveness reaches ca. 82% for both techniques.