A Local Adaptive Thresholding framework for image binarization written in C++, with JS and Python bindings. Implementing: Otsu, Bernsen, Niblack, Sauvola, Wolf, Gatos, NICK, Su, T.R. Singh, WAN, ISauvola, Bataineh, Chan and Shafait.
We need to document the parameter defaults for each algorithm, and other algorithms.
Create a Wiki that describes how to use the API and its options, along with how each Algorithm works.
Algorithm Parameters
Otsu
Bataineh
No parameters
Niblack
Sauvola
ISauvola
TRSingh
Wan
Wolf
name: "window", default: 75
name: "k", default: 0.2
NICK
name: "window", default: 75
name: "k", default: -0.2
Bernsen
name: "window", default: 75
name: "threshold", default: 100
name: "contrast-limit", default: 25
Gatos
name: "glyph", default: 60
Su *
name: "window", default: 0 = Auto-Detect
name: "minN", default: value of "window"
* Su - A "window" value of 0 will cause the algorithm to auto-detect based on stroke width. This is not currently implemented so a default value of 9 is currently being used.
We need to document the parameter defaults for each algorithm, and other algorithms. Create a Wiki that describes how to use the API and its options, along with how each Algorithm works.
Algorithm Parameters
PNM Parameters
This is for C++ only