Gradient direction analysis for contour tracking and local non maximum suppression

Manuel G. Forero; Miguel Á. González; Santiago Cortes; Vanesa V. Gómez

doi:10.1117/12.2596089

1 August 2021 Gradient direction analysis for contour tracking and local non maximum suppression

Manuel G. Forero, Miguel Á. González, Santiago Cortes, Vanesa V. Gómez

Proceedings Volume 11842, Applications of Digital Image Processing XLIV; 118422F (2021) https://doi.org/10.1117/12.2596089
Event: SPIE Optical Engineering + Applications, 2021, San Diego, California, United States

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Abstract

One of the most used techniques for edge refinement, once a convolution mask has been used, is the local non-maximum elimination method proposed by Canny. This technique uses the magnitude and direction of the gradient to determine whether a pixel is a local maximum. In addition, the direction of the gradient is used in a subsequent step, to perform contour enclosure in case any discontinuity is present. The local maximum detection technique gives good results when using masks of size 3 x 3 or larger. Deriche introduced an extension of Canny's edge detection method, which obtains state-of-the-art results, using a recursive method that only considers pixels in the vertical or horizontal direction for the calculation, which is equivalent to using linear operators of size 3 x 1 or larger. This technique allows good edge detection, in a shorter time, regardless of the filter size. Deriche mentions the need to employ a smoothing technique, obtained by integrating his derivative operator, prior to the use of the derivative operator. In this work the result obtained with this operator is compared with the Prewitt and Sobel and Feldman operators in the determination of the direction of the gradient to find the local maxima.

Citation Download Citation

Manuel G. Forero, Miguel Á. González, Santiago Cortes, and Vanesa V. Gómez "Gradient direction analysis for contour tracking and local non maximum suppression", Proc. SPIE 11842, Applications of Digital Image Processing XLIV, 118422F (1 August 2021); https://doi.org/10.1117/12.2596089

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