Abstract-An integrated methodology for the detection and removal of cracks on digitized images is presented in this paper. The cracks are detected by steepest descent algorithm (SDA) the output of the piping image as cracks are removed using either a gradient Function (GRF) and processed data or a semi-automatic procedure based on region growing. Finally, crack filling using the steepest descent algorithm. The methodology has been shown to perform very well on digitized images suffering from cracks, using Matlab, Surfer and Visual Fortran programming.

Abstract-This paper presents an application of the wavelet transform for damage detection or crack detection based on digital image processing measurements. A number of important issues that need to be considered when image sequences are used for vibration analysis are discussed. These include: correspondence of image features from image to image, image calibration and spatial resolution. The principles of image edge detection are discussed and a comparison between the wavelet approach and the classical method is presented. A digital image damage detection method based on converting image to data, then filtering and converting from 2D to 3D data measured. The method is illustrated using a simple programming for matlab and Fortran for image to data and wavelet transformation model. The major advantage of the method is the significantly increased number of discrete points used to describe mode shapes. This is in contrast to classical techniques where in practice a small number of measurement points are obtained from a limited number of sensors.