Difference between revisions of "Example Binary Image"
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In a binary image each pixel can have a value of 0 or 1. Binary images are easy to compute and fast to process, which makes them popular in many applications. BoofCV contains many operations for creating and manipulating binary images. The example below demonstrates a few of ones contained inside of BinaryImageOps. | In a binary image each pixel can have a value of 0 or 1. Binary images are easy to compute and fast to process, which makes them popular in many applications. BoofCV contains many operations for creating and manipulating binary images. The example below demonstrates a few of ones contained inside of BinaryImageOps. | ||
Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0. | Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/imageprocessing/ExampleBinaryOps.java ExampleBinaryOps.java] | ||
Concepts: | Concepts: | ||
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// convert into a usable format | // convert into a usable format | ||
GrayF32 input = ConvertBufferedImage.convertFromSingle(image, null, GrayF32.class); | |||
GrayU8 binary = new GrayU8(input.width,input.height); | |||
GrayS32 label = new GrayS32(input.width,input.height); | |||
// Select a global threshold using Otsu's method. | // Select a global threshold using Otsu's method. | ||
Line 53: | Line 53: | ||
// The null in the input indicates that it should internally declare the work image it needs | // The null in the input indicates that it should internally declare the work image it needs | ||
// this is less efficient, but easier to code. | // this is less efficient, but easier to code. | ||
GrayU8 filtered = BinaryImageOps.erode8(binary, 1, null); | |||
filtered = BinaryImageOps.dilate8(filtered, 1, null); | filtered = BinaryImageOps.dilate8(filtered, 1, null); | ||
Revision as of 20:42, 27 March 2016
In a binary image each pixel can have a value of 0 or 1. Binary images are easy to compute and fast to process, which makes them popular in many applications. BoofCV contains many operations for creating and manipulating binary images. The example below demonstrates a few of ones contained inside of BinaryImageOps.
Example File: ExampleBinaryOps.java
Concepts:
- Image Thresholding
- Morphological Operations
- Binary Labeling
- Pixel Math
- Image Rendering
Relevant Applets:
Basic Example
/**
* Demonstrates how to create binary images by thresholding, applying binary morphological operations, and
* then extracting detected features by finding their contours.
*
* @see boofcv.examples.segmentation.ExampleThresholding
*
* @author Peter Abeles
*/
public class ExampleBinaryOps {
public static void main( String args[] ) {
// load and convert the image into a usable format
BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("particles01.jpg"));
// convert into a usable format
GrayF32 input = ConvertBufferedImage.convertFromSingle(image, null, GrayF32.class);
GrayU8 binary = new GrayU8(input.width,input.height);
GrayS32 label = new GrayS32(input.width,input.height);
// Select a global threshold using Otsu's method.
double threshold = GThresholdImageOps.computeOtsu(input, 0, 255);
// Apply the threshold to create a binary image
ThresholdImageOps.threshold(input,binary,(float)threshold,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.
GrayU8 filtered = BinaryImageOps.erode8(binary, 1, null);
filtered = BinaryImageOps.dilate8(filtered, 1, null);
// Detect blobs inside the image using an 8-connect rule
List<Contour> contours = BinaryImageOps.contour(filtered, ConnectRule.EIGHT, label);
// colors of contours
int colorExternal = 0xFFFFFF;
int colorInternal = 0xFF2020;
// display the results
BufferedImage visualBinary = VisualizeBinaryData.renderBinary(binary, false, null);
BufferedImage visualFiltered = VisualizeBinaryData.renderBinary(filtered, false, null);
BufferedImage visualLabel = VisualizeBinaryData.renderLabeledBG(label, contours.size(), null);
BufferedImage visualContour = VisualizeBinaryData.renderContours(contours, colorExternal, colorInternal,
input.width, input.height, null);
ListDisplayPanel panel = new ListDisplayPanel();
panel.addImage(visualBinary, "Binary Original");
panel.addImage(visualFiltered, "Binary Filtered");
panel.addImage(visualLabel, "Labeled Blobs");
panel.addImage(visualContour, "Contours");
ShowImages.showWindow(panel,"Binary Operations",true);
}
}