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A new article is available in IPOL:
<a class="moz-txt-link-freetext" href="http://www.ipol.im/pub/art/2015/35/">http://www.ipol.im/pub/art/2015/35/</a><br>
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Haldo Spontón, and Juan Cardelino, <br>
A Review of Classic Edge Detectors, <br>
Image Processing On Line, 5 (2015), pp. 90–123. <br>
<a class="moz-txt-link-freetext" href="http://dx.doi.org/10.5201/ipol.2015.35">http://dx.doi.org/10.5201/ipol.2015.35</a><br>
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Abstract<br>
In this paper some of the classic alternatives for edge detection in
digital images are studied. The main idea behind edge detection is
to find where abrupt changes in the intensity of an image have
occurred. The first family of algorithms reviewed in this work uses
the first derivative to find the changes of intensity, such as
Sobel, Prewitt and Roberts. In the second reviewed family it is used
second derivative, for example in algorithms like Marr-Hildreth and
Haralick. Results obtained from a qualitative point of view
(perceptual) and from a quantitative point of view (number of
operations, execution time) are compared, considering different ways
to convolve an image with a kernel (step required in some of the
algorithms).<br>
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