Automated Sewer Pipe Inspection through Image Processing
نویسندگان
چکیده
An innovative inspection method to assess the condition of sewer pipes is proposed in this paper. The standard sewer inspection technique, based on closed-circuit television systems, has a very poor performance. A video camera is mounted on a robot and the video recording is provided off-line to an engineer that classifies the potential defects. The focus of the research is the automated identification and location of discontinuities in the internal surface of sewers. The transducer used is an assembly of a CCD camera and optics elements to generate a ring-shaped laser pattern. The automated inspection method consists of several stages including the segmentation of the image into characteristic geometric features and potential defect regions. Automatic recognition, rating and classification of pipe defects are carried out by means of computation of a partial histogram based on adaptive image processing. Experiments in a realistic environment have been conducted and results are presented.
منابع مشابه
Automated Sewer Inspection Using Image Processing and a Neural Classifier
The focus of the research presented here is on the automated assessment of sewer pipe conditions using a laserbased sensor. The proposed method involves image and data processing algorithms categorising signals acquired from the internal pipe surface. Fault identification is carried out using a neural network. Experimental results are presented.
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