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The "voids-and-cluster" method gets its name from the matrix generation procedure, where a black image with randomly initialized white pixels is gaussian-blurred to find the brightest and darkest parts, corresponding to voids and clusters. After a few swaps have evenly distributed the bright and dark parts, the pixels are numbered by importance.
Top: Traditional scaling, corners are distorted. Bottom: 9-slice scaling, corners aren't distorted. 9-slice scaling (also known as Scale 9 grid, 9-slicing or 9-patch) is a 2D image resizing technique to proportionally scale an image by splitting it in a grid of nine parts.
It helps the user to distinguish the selection border from the image background by animating the border. The border is a dotted or dashed line where the dashes seem to move slowly sideways and up and down. This creates an illusion of ants marching in line as the black and white parts of the line start to move.
The term dither was published in books on analog computation and hydraulically controlled guns shortly after World War II. [1] [2] [nb 1] Though he did not use the term dither, the concept of dithering to reduce quantization patterns was first applied by Lawrence G. Roberts [4] in his 1961 MIT master's thesis [5] and 1962 article. [6]
Midnight Commander using box-drawing characters in a terminal emulator. Box-drawing characters, also known as line-drawing characters, are a form of semigraphics widely used in text user interfaces to draw various geometric frames and boxes.
The silhouette value is a measure of how similar an object is to its own cluster (cohesion) compared to other clusters (separation). The silhouette ranges from −1 to +1, where a high value indicates that the object is well matched to its own cluster and poorly matched to neighboring clusters.
The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]
After the clusters are located, typically the points in each cluster are averaged to obtain the representative color that all colors in that cluster are mapped to. The three color channels are usually red, green, and blue, but another popular choice is the Lab color space, in which Euclidean distance is more consistent with perceptual difference.