Abstract
In this paper, we denote a color image by a quaternion function, then find edge points by solving the maximum of quaternion fractional directional differentiation(QFDD)’s norm. This method is called edge detection based on QFDD. Experiments indicate that the method has special advantages. Comparing with Canny, LOG, Sobel, and general fractional differentiation, we discover that QFDD has fewer false negatives in the textured regions and is also better at detecting edges which are partially defined by texture, which means we will obtain better results in the interesting regions by QFDD and these results are more consistent with the characteristics of human visual system.
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Gao, C., Zhou, J., Lang, F., Pu, Q., Liu, C. (2011). A Novel Approach to Edge Detection of Color Image Based on Quaternion Fractional Directional Differentiation. In: Lee, G. (eds) Advances in Automation and Robotics, Vol.1. Lecture Notes in Electrical Engineering, vol 122. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25553-3_22
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DOI: https://doi.org/10.1007/978-3-642-25553-3_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25552-6
Online ISBN: 978-3-642-25553-3
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