Abstract :
Automatic edge detection is a highly researched field because it is used in many different applications in image processing, such as diagnosis in medical imaging, topographical recognition and automated inspection of machine assemblies. Historically, the Discrete Wavelet Transform (DWT) has been a successful technique used in edge detection. The contributions of new, recent work in this area are examined and summarized concisely. Utilizing multiple phases, such as de-noising, preprocessing, thresholding coefficients, smoothing, and postprocessing, are suggested for use with multiple iterations of the DWT in this research. The DWT is combined with various other methods for an optimal solution for the edge detection problem. This synopsis consolidates recent, related work into one source.
Keywords :
discrete wavelet transforms; edge detection; image denoising; image segmentation; smoothing methods; DWT; automatic edge detection; discrete wavelet transform; image de-noising; image postprocessing; image preprocessing; image smoothing; image thresholding coefficients; Biomedical imaging; Computer science; Detectors; Discrete wavelet transforms; Filters; Image edge detection; Image processing; Image recognition; Noise reduction; Smoothing methods;
