Underground pipelines are the country’s one of the largest investment. The use of these underground pipelines are mainly for the water supply and also for sewage purpose. But the condition of these pipelines is generally unknown unless some type of failure occurs. Billions of dollars have been spent in North America for the maintenance of the underground sewage system. But the condition of these pipelines is continuous decline due to the ill maintenance and also due to the chemicals present in the wastewater react with the pipes and make the things even worse.
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For the above problem, many solutions have been tried and failed because they are inspected only after the failure of the pipes. This will result in difficult and costly rehabilitation. Presently, the condition of the underground pipes is assessed by using CCTV. This process is also failed because the videos archiving and access to these are very time consuming and also expensive. To develop this condition of maintenance of the underground pipelines an automatic pipe detection system is required to assess the information and also ensure the accuracy, economy of the pipe examination, and efficiency.
Software and hardware components
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The inspection of the underground pipelines has advanced but the process remained the same. The basic process is the technician has to identify pipe defects on a monitor and find the defect according to the level of deterioration and risk. This process is very effective only if the length of the pipeline is small. In this project, you will be dealing with the automation of this method using image processing techniques. In this project, we will be using morphological filtering for processing the digital images based on the shape. The following steps are involved in this project:
In this way, the pipeline defect detection is done automatically and more accurately using image processing. This will help the government in saving funds and also the time as well.
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