IMAGEMAGICK MERGE PDF

Layering Images Introduction As we have previously noted, ImageMagick does not deal with just one image, but a sequence or list of images. This allows you to use IM in two very special image processing techniques. You can for example think of each image in the list as a single frame in time, so that the whole list can be regarded as being a Animation. This will be explored in other IM Example Pages. See Animation Basics. Alternatively, you can think of each image in the sequence as Layers of a set of see-through overhead transparencies.

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ImageMagick 1. Back to Contents Segmentation Use -segment to segment an image by analyzing the histograms of the color components and identifying units that are homogeneous with the fuzzy c-means technique.

The scale-space filter analyzes the histograms of the three color components of the image and identifies a set of classes. The extents of each class is used to coarsely segment the image with thresholding. The color associated with each class is determined by the mean color of all pixels within the extents of a particular class. Finally, any unclassified pixels are assigned to the closest class with the fuzzy c-means technique.

The fuzzy c-Means algorithm can be summarized as follows: Build a histogram, one for each color component of the image. For each histogram, successively apply the scale-space filter and build an interval tree of zero crossings in the second derivative at each scale.

Analyze this scale-space "fingerprint" to determine which peaks or valleys in the histogram are most predominant. The fingerprint defines intervals on the axis of the histogram. Each interval contains either a minima or a maxima in the original signal. If each color component lies within the maxima interval, that pixel is considered "classified" and is assigned an unique class number.

Any pixel that fails to be classified in the above thresholding pass is classified using the fuzzy c-Means technique. It is assigned to one of the classes discovered in the histogram analysis phase. The fuzzy c-Means technique attempts to cluster a pixel by finding the local minima of the generalized within group sum of squared error objective function.

A pixel is assigned to the closest class of which the fuzzy membership has a maximum value. Used when formatting text for the screen. Many Unix systems keep this shell variable up to date, but it may need to be explicitly exported in order for ImageMagick to see it.

This path allows the user to arbitrarily extend the image formats supported by ImageMagick by adding loadable modules to an arbitrary location rather than copying them into the ImageMagick installation directory.

The formatting of the search path is similar to operating system search paths i. This user specified search path is used before trying the default search path.

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