  This paper presents an edge detection method based on global and local
parameters of the image, which produces satisfactory results on the edge
detection of complex images and has a simple structure for execution. The local
and global parameters of the image are arithmetic means and standard
deviations, the former acquired from a three sized window representing five
pixels, the latter acquired from the entire row or column. We obtain the
differences of grayscale intensities between two adjacent pixels and the sum of
the modulus of these differences from the horizontal and vertical scans of the
image. Using these obtained values, we calculate the local and global
parameters. After the gathering of the local and global parameters, we compare
each sum of the modulus of differences with its own local and global parameter.
In the case of the comparison is true, the consecutive pixel to the modulus sum
of differences index is marked as an edge. We present the results of the tests
with grayscale images using different parameters and discuss the advantages and
disadvantages of each parameter value and algorithm structure chosen on the
edge processing. There is a comparison of results between this papers detector
and Canny, where we evaluate the quality of the presented detector.
