Difference between revisions of "Example Binary Image"
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		binary = BinaryImageOps.dilate8(binary, null);  | 		binary = BinaryImageOps.dilate8(binary, null);  | ||
		//   | 		// Detect blobs inside the binary image and assign labels to them  | ||
		int numBlobs = BinaryImageOps.labelBlobs4(binary,blobs);  | 		int numBlobs = BinaryImageOps.labelBlobs4(binary,blobs);  | ||
Revision as of 10:51, 18 October 2011
Binary Image Processing
Binary images are images where each pixel can take on two values, typically represented by 0 or 1. Binary images are easy to compute and fast to process, which makes them popular in many applications.
Example File: BinaryImageExample.java
Concepts:
- Image Thresholding
 - Morphological Operations
 - Binary Labeling
 - Pixel Math
 - Image Rendering
 
Basic Example
In this example a threshold is computed for the input image dynamically and the resulting binary image shown.
	public static void binaryExample( BufferedImage image )
	{
		// convert into a usable format
		ImageFloat32 input = ConvertBufferedImage.convertFrom(image,null,ImageFloat32.class);
		ImageUInt8 binary = new ImageUInt8(input.width,input.height);
		// the mean pixel value is often a reasonable threshold when creating a binary image
		float mean = PixelMath.sum(input)/(input.width*input.height);
		// create a binary image
		ThresholdImageOps.threshold(input,binary,mean,true);
		// Render the binary image for output and display it in a window
		BufferedImage visualBinary = VisualizeBinaryData.renderBinary(binary,null);
		ShowImages.showWindow(visualBinary,"Binary Image");
	}
Labeled Example
Here clustered of blobs are detected and arbitrarily assigned labels.
	public static void labeledExample( BufferedImage image )
	{
		// convert into a usable format
		ImageFloat32 input = ConvertBufferedImage.convertFrom(image,null,ImageFloat32.class);
		ImageUInt8 binary = new ImageUInt8(input.width,input.height);
		ImageSInt32 blobs = new ImageSInt32(input.width,input.height);
		// the mean pixel value is often a reasonable threshold when creating a binary image
		float mean = PixelMath.sum(input)/(input.width*input.height);
		// create a binary image
		ThresholdImageOps.threshold(input,binary,mean,true);
		// remove small blobs through erosion and dilation
		// The null in the input indicates that it should internally declare the work image it needs
		// this is less efficient, but easier to code.
		binary = BinaryImageOps.erode8(binary,null);
		binary = BinaryImageOps.dilate8(binary, null);
		// Detect blobs inside the binary image and assign labels to them
		int numBlobs = BinaryImageOps.labelBlobs4(binary,blobs);
		// Render the binary image for output and display it in a window
		BufferedImage visualized = VisualizeBinaryData.renderLabeled(blobs, numBlobs, null);
		ShowImages.showWindow(visualized,"Labeled Image");
	}