Feature Extraction of Sewer Pipe Defects Using Wavelet Transform and Co-Occurrence Matrix

In general, the sewer inspection usually employs a great number of CCTV images to discover sewer failures by human interpretation. A computer-aided program remains to be developed due to human’s fatigue and subjectivity. To enhance the efficiency of sewer inspection, this paper attends to apply artificial intelligence to extract the failure features of the sewer systems that is demonstrated on the sewer system in the eastern Taichung City, Taiwan. Wavelet transform and gray-level co-occurrence matrix, which have been widely applied in many texture analyses, are adopted in this research to generate extracted features, which are the most valuable information in pattern recognition of failures on CCTV images. Wavelet transform is capable of dividing an image into