Image Processing Toolbox
Image analysis is the process of extracting meaningful information from images such as finding shapes, counting objects, identifying colors, or measuring object properties.
Image Processing Toolbox provides a comprehensive suite of reference-standard algorithms and visualization functions for image analysis tasks such as statistical analysis, feature extraction, and property measurement.
Image transforms play a critical role in many image processing tasks, including image enhancement, analysis, restoration, and compression. Image Processing Toolbox provides several image transforms, including Hough, Radon, FFT, DCT, and fan-beam projections. You can reconstruct images from parallel-beam and fan-beam projection data (common in tomography applications).
Image transforms are also available in MATLAB and Wavelet Toolbox™.
The Hough transform is designed to identify lines and curves within an image. Using the Hough transform you can:
Statistical functions let you analyze the general characteristics of an image by:
Device-independent color management enables you to accurately represent color independently from input and output devices. This is useful when analyzing the characteristics of a device, quantitatively measuring color accuracy, or developing algorithms for several different devices. With specialized functions in the toolbox, you can convert images between device-independent color spaces, such as sRGB, XYZ, xyY, L*a*b*, uvL, and L*ch.