![]() ![]() Least it is without a directional bias, or pixel duplication/loss. Of course this does makes the spread more pronounced, and less linear, but at \( clone spread 5 -transverse -spread 5 -transverse \) \ But in the mean time you canĪt least mitigate the directional bias by doing the spread twice, with a the This problem is more pronounce when you use a smallerĪ solution to this double-swap problem is not easy, and we are looking forĪ 'limited area shuffle' algorithm to solve it. Note how some red pixels are spread downward more, though you also get a fewīlue pixels spreading upward more than expected too ( though toward the left \( clone spread 5 \) append spread_bias.png That movement is of course balanced butĪ smaller drift of a large number of pixels toward the upper-left.įor example, here I spread pixels with the original prepended as a referance.Ĭonvert -size 40x40 xc:red xc:blue -append \ This double swapping also mean that pixels were likely to spread further That means a specific pixel could drift further than was That is a specific pixel may be swapped, but then selected to be swapped again However due to the way pixels are processed, pixels may be 'double-swapped'. Image is still present, just displaced to to new location. Pixel in the image will be duplicated or lost. Means a specific pixel in the image may become duplicated or lost.Īs of IM v6.9.2-2 you can use " spread" to actually swap pixels within the image, meaning that no That is the pixels are not 'swapped' but randomally copied, which The main problem with the above is that you can lose some pixel data from the Virtual pixels and posible 'edge color bias', I recommend you use " -virtual-pixel Mirror".Īs such this is a more traditonal random 'spread' of pixels.Ĭonvert rose: -interpolate nearest -virtual-pixel mirror \ Mixing by forcing the color lookup of specific pixels by using " -interpolate Nearest". To get a more traditional spread pixels effect, you can prevent this color The real pixels of the image and virtual pixels. Pixels Though there are a few grey pixels interpolated from the border between This is more pronounce smaller distance values.Ĭonvert -size 80x80 xc: -virtual-pixel black -spread 10 spread_virtual.pngĪs you can see you get a randomized border, mostly of pure black virtual That is they are interpolated, not simply spread If you were to examine the pixels image you will see that some pixels may haveĪ mix of red and blue colors. This random selection was made as per the use of Pixel Interpolation and Virtual-Pixel Setting.Ĭonvert -size 80x40 xc:red xc:blue -append -spread 5 spread_interpolated.png Replace each pixel the color of a random nearby color from the source image. This is probably easier, though prehaps not as versatile.Ĭonvert rose: -bordercolor green -shave 6圆 -border 6圆 inside_border2.jpg If you don't know the size of the image, then you can Shave the image then add the Border as The width of the border added is controlled by the " -strokewidth" of theĪs such the above 6 pixel border needed a " -strokewidth" of 11. draw 'rectangle 0,0 69,45' inside_border.jpg As the built in rose in is 70x46 pixels, this isĬonvert rose: -fill none -stroke navy -strokewidth 11 \ Rather than adding a border around the outside of an image an user wanted toĪdd one to overlay the edges of an image. The operator only works on rectangular images, and will fail for images withĪ transparent background, as the color modifications will also be transparent. This operator is a bit like Framing an image,īut instead of adding extra pixels as a border, the " -raise" operator re-colors theĮdge pixels of the image. All it does isĪs a rectangular bevel highlight to an existing image.Īn inverted sunken effect can be generated using the 'plus' form of the Such a simple image transformation, that it almost isn't. Image has changed, often dramatically, the original image itself is stillĪrt-Like Transformations Raise or Sunk Borders These operations produce major changes to the overall appearance of the imageĮither for visual, or art-like effects. Function, Multi-Argument Evaluate Polynomial, Sinusoid, ArcSin, ArcTan Mathematics on Gradients.Accessing data from other images Evaluate and Function, Fast FX Operators.Using a Dawn Shade Highlight Using FX, the DIY Image Operator.Local Adaptive Thresholding (lat) Shade 3D Highlighting.Edging Using a Raster to Vector Converter.Spacing out Tiles Computer Vision Transformations.Stegano, hiding a secrets within an image.Turn images into raised or sunken buttons.Index ImageMagick Examples Preface and Index Art-like Transformations ![]()
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