Image Analysis

Image processing techniques for image analysis

Image analysis involves processing an image into fundamental components in order to extract statistical data. Image analysis can include such tasks as finding shapes, detecting edges, removing noise, counting objects, and measuring region and image properties of an object.

Image analysis is a broad term that covers a range of techniques that generally fit into these subcategories:

Here are examples of these image processing techniques:

Enhancing grayscale images with histogram equalization.

Segmenting images using Sobel Edge detection method.

Removing noise with morphological operations like image opening.

Extracting statistical data using the Image Region Analyzer.

You can perform image analysis in MATLAB® with the Image Processing Toolbox™, which provides image processing algorithms, tools, and a comprehensive environment for data analysis, visualization, and algorithm development.

See also: color profile, image thresholding, image enhancement, image reconstruction, image segmentation, image transform, image registration, digital image processing, image processing and computer vision, Steve on Image Processing, affine transformation, lab color