文献类型：会议论文

英文题名：Sewage Image Feature Extraction and Turbidity Degree Detection Based on Embedded System

作者：Gao, Meijuan[1,2];Tian, Jingwen[1,2];Ai, Lan[1];Zhang, Fan[2]

第一作者：Gao, Meijuan;高美娟

通讯作者：Gao, MJ[1]

机构：[1]Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China;[2]Beijing Univ Chem Technol, Sch Informat Sci, Beijing, Peoples R China

第一机构：北京联合大学城市轨道交通与物流学院

通讯机构：[1]corresponding author), Beijing Union Univ, Dept Automat Control, Beijing, Peoples R China.|[1141751]北京联合大学城市轨道交通与物流学院;[11417]北京联合大学;

会议论文集：International Conference on MultiMedia and Information Technology

会议日期：DEC 30-31, 2008

会议地点：Three Gorges, PEOPLES R CHINA

语种：英文

外文关键词：embedded system; sewage treatment; image feature extraction; sewage turbidity degree; detection

摘要：Sewage turbidity degree is an important judgment standard of primary processed wastewater. Embedded system (ARM) platform has excellences of low power consumption, dexterity, good community ability. A detection method of sewage turbidity degree based on ARM is proposed. The image sensors and tight intensity are used to combine with ARM system and obtain the sewage image, and a kind of image gather and analyzing system is composed. The edge detection algorithm and image enhancement of image processing are used to treat the obtained image. We extract sewage turbidity degree characters and judge whether the sewage image is qualified, and realize image detection algorithm on ARM system. ARM system judges sewage qualified or not based on result of image detection arithmetic and information of light intensity sensor. The method is validated by simulation on ARM platform.