Analyzing images using image thresholding techniques
Image thresholding is a simple, yet effective, way of partitioning an image into a foreground and background. This image analysis technique is a type of image segmentation that isolates objects by converting grayscale images into binary images. Image thresholding is most effective in images with high levels of contrast.
Common image thresholding algorithms include histogram and multi-level thresholding.
Image thresholding using multi-level thresholding
Image thresholding using a set level
For more detail, see Image Processing Toolbox.
Examples and How To
-
-
-
Indexing Segmented Objects and Connected Components (Blog Posts)
Software Reference
- Segmentation and Thresholding (Function List)
- Object Analysis (Function List)
- Morphological Filtering (Function List)
- Integrating MATLAB and C/C++
See also: color profile, image analysis, image enhancement, image reconstruction, image segmentation, image transform, digital image processing, image processing and computer vision, Steve on Image Processing, edge detection, image registration, affine transformation, lab color
