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Diffstat (limited to 'julia/scharr.jl')
| -rw-r--r-- | julia/scharr.jl | 37 |
1 files changed, 37 insertions, 0 deletions
diff --git a/julia/scharr.jl b/julia/scharr.jl new file mode 100644 index 0000000..02daeb6 --- /dev/null +++ b/julia/scharr.jl @@ -0,0 +1,37 @@ +# -*- coding: utf-8 -*- +# +# Calculate the derivatives of an image using the Scharr operator +# of kernal size 3x3. +# +# References: +# [1] https://en.wikipedia.org/wiki/Sobel_operator +# [2] http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/sobel_derivatives/sobel_derivatives.html +# +# Aaron LI +# 2015/07/20 +# + +# Calculate the derivatives of the image using the Scharr operator +# img - input image +# dx - order of the derivative x +# dy - order of the derivative y +function scharr(img, dx, dy) + rows, cols = size(img) + img_d = float(img) + (isa(dx, Int) && dx >= 0) || error("dx should be an integer >= 0") + (isa(dy, Int) && dy >= 0) || error("dy should be an integer >= 0") + # Scharr operator + Gy = [-3.0 -10.0 -3.0; 0.0 0.0 0.0; 3.0 10.0 3.0]; + Gx = Gy' + # calculate the derivatives using convolution + for i = 1:dx + img_d = conv2(img_d, Gx) + end + for i = 1:dy + img_d = conv2(img_d, Gy) + end + # FIXME: 'conv2' will increase the image size + rows_d, cols_d = size(img_d) + return img_d[(div(rows_d-rows, 2)+1):(div(rows_d-rows, 2)+rows), (div(cols_d-cols, 2)+1):(div(cols_d-cols, 2)+cols)] +end + |