Image Processing Toolbox

Image Analysis

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

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™.


Reconstructing an Image from Projection Data
Comparing the reconstruction of an image using parallel (Radon) and fan-beam geometries.

Hough Transform

The Hough transform is designed to identify lines and curves within an image. Using the Hough transform you can:

  • Find line segments and endpoints
  • Measure angles
  • Find circles based on size

Statistical Functions

Statistical functions let you analyze the general characteristics of an image by:

Device-Independent Color Management

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.

Next: Image Segmentation

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Image Processing Made Easy

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