components, an Octave code which organizes contiguous cells into labeled clusters, for a 1D, 2D, or 3D array. This code has uses in image analysis and percolation simulation.
The computer code and data files described and made available on this web page are distributed under the MIT license
components is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.
bwlabel_test, an Octave code which calls bwlabel(), which is a built-in MATLAB function, which is given a binary matrix, and organizes the 1 values into labeled clusters, using 4-way or 8-way connectivity.
image_boundary, an Octave code which reports the pixels which form the boundary between the black and white regions of a simple image.
image_contrast, an Octave code which applies image processing techniques to increase the contrast in an image.
image_decimate, an Octave code which compresses an image by dropping the even rows and columns of data.
image_denoise, an Octave code which applies image processing techniques to remove noise from an image.
image_diffuse, an Octave code which uses diffusion to smooth out an image.
image_double, an Octave code which doubles the height and width of an image by repeating each row and column.
image_edge, an Octave code which demonstrates a simple procedure for edge detection in images.
image_noise, MATLAB codes which add noise to an image.
image_quantization, an Octave code which demonstrates how the KMEANS algorithm can be used to reduce the number of colors or shades of gray in an image.
image_rgb_to_gray, a MATLAB function which creates a grayscale version of an RGB image.
image_threshold, an Octave code which creates a black and white version of a grayscale image by specifying a single threshold value; pixels below this value become black, and above this value they are white.
MathWorks documentation for the Image Processing Toolbox is available at https://www.mathworks.com/access/helpdesk/help/pdf_doc/images/images_tb.pdf.