Edge detection is an important step in image processing. As edge is
intensity variation with spatial coordinates, the similarities between neighboring
pixels could be used for edge detection. It has been observed that the
effective results could be attained by thresholding the homogeneity images
generated by means of the similarity transformation. Nevertheless, the
user-defined normalization coefficient in similarity transform stage seriously
effects edge detection performance and it needs to be automatically selected
for every particular image. In this study, a new approach in which the
normalization coefficient is automatically determined has been presented. The
automating process of the similarity transform has been performed according to
the gray level values of the neighboring pixels. The gray level differences of
the central pixel and other neighboring pixels have been used to determine the
similarity coefficient. Subsequently, the binarization process of the
homogeneity images obtained with proposed algorithm have been completed with
different thresholding techniques. Additionally, the F-score of the proposed
edge detection has been obtained with 200 images in the BSDS training dataset.
The achieved F-score values have showed that the performance of automatic
approach is quite high.
Primary Language | English |
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Subjects | Engineering |
Journal Section | Computer Engineering |
Authors | |
Publication Date | June 1, 2019 |
Published in Issue | Year 2019 Volume: 32 Issue: 2 |