The Wavelet transform is a mathematical tool that is booming since the mid-80s of the twentieth century, because it is more efficient than the classical Fourier transform in the field of investigation in digital signal processing and imaging. Its applications are many, among which are: Analysis of noise, signal compression, extraction of edges (details diagonals, vertical and horizontal digital images), and key features for optimal extraction of contours. This article analyzes and describes the computational implementation, using models and processes (signatures and counting pixels) of the computer visualization of the degree of coincidence of contours in images, from the comparison of parameters such as area, perimeter, compactness, and diameter contours. The implementation presented is done by programming functions for the development of the wavelet transform included in the softwareMatlab 7.1 ®.