2.6.4.3 imgBinary

1 Menu Information
2 Brief Information
3 Command Line Usage
4 X-Function Execution Options
5 Variables
6 Description
7 Examples
8 Algorithm
9 References
10 Related X-Functions

Menu Information

Image: Conversion: Binary

Brief Information

Convert image to binary

Command Line Usage

1. imgBinary t1:=30 t2:=160 c:=red oimg:=mat(2);

2. imgBinary img:=[Mbook1]Msheet1!Mat(1) oimg:=<new>;

X-Function Execution Options

Please refer to the page for additional option switches when accessing the x-function from script

Variables

Display Name	Variable Name	I/O and Type	Default Value	Description
Input Matrix	img	Input Image	<active>	Specifies the image to be manipulated. The default input is the active image.
Low	t1	Input int		Specifies the lowest intensity to be detected. Possible values range from 0 to 255.
High	t2	Input int		Specifies the highest intensity to be detected. Possible values range from 0 to 255.
Channel	c	Input int	RGB	Specifies the color channel to process. Option list rgb:RGB RGB channels. red:Red Red channel only. green:Green Green channel only. blue:Blue Blue channel only.
Output Image	oimg	Output Image	<input>	Specifies the output image. By default, the output image is the same as the input image. See the syntax here.

Description

This X-Function converts the input image into a binary image by separating the image pixels using thresholds. You can define the thresholds with the variables, Low and High. Any pixels with intensity lower than the value of the Low variable and any pixels with intensity higher than the value of the High variable will be set to 0, which represents the black color. Other pixels will be set to the white color.

Examples

In this example, we use the imgBinary function to convert the input image into a binary one:

When the input image is active, select Image: Conversion: Binary. This opens the dialog of the X-Function.
In the X-Function dialog, change the settings as the screenshot below and click OK to close the dialog.

A new image is created. We can see that it is monochromatic.


The original image	The output image

Algorithm

The computation uses L_IntensityDetectBitmap() function from LEADTOOLS Main API. Please refer to the LEADTOOLS Main API Help file, Version 14 and read the L_IntensityDetectBitmap topic.