Balanced histogram thresholding, the Glossary
In image processing, the balanced histogram thresholding method (BHT), is a very simple method used for automatic image thresholding.[1]
Table of Contents
7 relations: C (programming language), Digital image processing, Histogram, Otsu's method, Python (programming language), Thresholding (image processing), Weighing scale.
- Image segmentation
C (programming language)
C (pronounced – like the letter c) is a general-purpose programming language.
See Balanced histogram thresholding and C (programming language)
Digital image processing
Digital image processing is the use of a digital computer to process digital images through an algorithm.
See Balanced histogram thresholding and Digital image processing
Histogram
A histogram is a visual representation of the distribution of quantitative data.
See Balanced histogram thresholding and Histogram
Otsu's method
In computer vision and image processing, Otsu's method, named after, is used to perform automatic image thresholding. Balanced histogram thresholding and Otsu's method are image segmentation.
See Balanced histogram thresholding and Otsu's method
Python (programming language)
Python is a high-level, general-purpose programming language.
See Balanced histogram thresholding and Python (programming language)
Thresholding (image processing)
In digital image processing, thresholding is the simplest method of segmenting images. Balanced histogram thresholding and thresholding (image processing) are image segmentation.
See Balanced histogram thresholding and Thresholding (image processing)
Weighing scale
A scale or balance is a device used to measure weight or mass.
See Balanced histogram thresholding and Weighing scale
See also
Image segmentation
- Amira (software)
- Aphelion (software)
- Avizo (software)
- Balanced histogram thresholding
- GrabCut
- Graph cuts in computer vision
- GrowCut algorithm
- Ilastik
- Image segmentation
- Insight Segmentation and Registration Toolkit
- Lambda-connectedness
- Livewire Segmentation Technique
- Medical image computing
- Minimum spanning tree-based segmentation
- Mumford–Shah functional
- Object co-segmentation
- Otsu's method
- Random walker algorithm
- Range segmentation
- Region growing
- Rigid motion segmentation
- Scale-space segmentation
- Segmentation-based object categorization
- Simple interactive object extraction
- Split and merge segmentation
- Statistical region merging
- Thresholding (image processing)
- Watershed (image processing)
- YaDICs
References
[1] https://en.wikipedia.org/wiki/Balanced_histogram_thresholding