Example Template Matching - Revision history

Peter at 23:19, 17 January 2022

2022-01-17T23:19:38Z

← Older revision		Revision as of 23:19, 17 January 2022
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	</center>		</center>

	Template matching compares a smaller image (the template) against every possible location in a larger target image. A match is declared the fit score is a local peak and above a threshold. Typically template matching is only used in highly controlled environments and doesn't work to well in natural scenes. It's also extremely computationally expensive and larger images/templates are likely to take an excessive amount of time to process.		Template matching compares a smaller image (the template) against every possible location in a larger target image. A match is declared the fit score is a local peak and above a threshold. Typically template matching is only used in highly controlled environments and doesn't work to well in natural scenes. It's also extremely computationally expensive and larger images/templates are likely to take an excessive amount of time to process.

	The example below is intended to demonstrate the strengths and weaknesses of template matching. For each template the number of matches returned needs to be specified. If the number of matches is known then the results are good in this example, but if too many are requested the some of the results are noise. The intensity image is shown for a match. Notice how ambiguous the results are.		The example below is intended to demonstrate the strengths and weaknesses of template matching. For each template the number of matches returned needs to be specified. If the number of matches is known then the results are good in this example, but if too many are requested the some of the results are noise. The intensity image is shown for a match. Notice how ambiguous the results are.

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/recognition/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/main/java/boofcv/examples/recognition/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	// create output image to show results		// create output image to show results
	~~BufferedImage~~ output = new BufferedImage(image.width, image.height, BufferedImage.TYPE_INT_BGR);		var output = new BufferedImage(image.width, image.height, BufferedImage.TYPE_INT_BGR);
	ConvertBufferedImage.convertTo(image, output);		ConvertBufferedImage.convertTo(image, output);
	Graphics2D g2 = output.createGraphics();		Graphics2D g2 = output.createGraphics();

Peter at 19:32, 12 July 2021

2021-07-12T19:32:43Z

← Older revision		Revision as of 19:32, 12 July 2021
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/~~features~~/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/recognition/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:

Peter at 19:10, 12 July 2021

2021-07-12T19:10:28Z

← Older revision		Revision as of 19:10, 12 July 2021
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	<syntaxhighlight lang="java">		<syntaxhighlight lang="java">
	/**		/**
	* Example of how to find objects inside an image using template matching. Template matching works		* Example of how to find objects inside an image using template matching. Template matching works
	* well when there is little noise in the image and the object's appearance is known and static. It can		* well when there is little noise in the image and the object's appearance is known and static. It can
	* also be very slow to compute, depending on the image and template size.		* also be very slow to compute, depending on the image and template size.
	*		*
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	* Demonstrates how to search for matches of a template inside an image		* Demonstrates how to search for matches of a template inside an image
	*		*
	* @param image Image being searched		* @param image Image being searched
	* @param template Template being looked for		* @param template Template being looked for
	* @param mask Mask which determines the weight of each template pixel in the match score		* @param mask Mask which determines the weight of each template pixel in the match score
	* @param expectedMatches Number of expected matches it hopes to find		* @param expectedMatches Number of expected matches it hopes to find
	* @return List of match location and scores		* @return List of match location and scores
	*/		*/
	private static List<Match> findMatches(GrayF32 image, GrayF32 template, GrayF32 mask,		private static List<Match> findMatches( GrayF32 image, GrayF32 template, GrayF32 mask,
	int expectedMatches) {		int expectedMatches ) {
	// create template matcher.		// create template matcher.
	TemplateMatching<GrayF32> matcher =		TemplateMatching<GrayF32> matcher =
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	// Find the points which match the template the best		// Find the points which match the template the best
	matcher.setImage(image);		matcher.setImage(image);
	matcher.setTemplate(template, mask,expectedMatches);		matcher.setTemplate(template, mask, expectedMatches);
	matcher.process();		matcher.process();

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	* a better match to the template.		* a better match to the template.
	*/		*/
	private static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {		private static void showMatchIntensity( GrayF32 image, GrayF32 template, GrayF32 mask ) {
	// create algorithm for computing intensity image		// create algorithm for computing intensity image
	TemplateMatchingIntensity<GrayF32> matchIntensity =		TemplateMatchingIntensity<GrayF32> matchIntensity =
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	}		}

	public static void main(String[] args) {		public static void main( String[] args ) {
	// Load image and templates		// Load image and templates
	String directory = UtilIO.pathExample("template");		String directory = UtilIO.pathExample("template");

	GrayF32 image = UtilImageIO.loadImage(directory ,"desktop.png", GrayF32.class);		GrayF32 image = UtilImageIO.loadImage(directory, "desktop.png", GrayF32.class);
	GrayF32 templateCursor = UtilImageIO.loadImage(directory , "cursor.png", GrayF32.class);		GrayF32 templateCursor = UtilImageIO.loadImage(directory, "cursor.png", GrayF32.class);
	GrayF32 maskCursor = UtilImageIO.loadImage(directory , "cursor_mask.png", GrayF32.class);		GrayF32 maskCursor = UtilImageIO.loadImage(directory, "cursor_mask.png", GrayF32.class);
	GrayF32 templatePaint = UtilImageIO.loadImage(directory , "paint.png", GrayF32.class);		GrayF32 templatePaint = UtilImageIO.loadImage(directory, "paint.png", GrayF32.class);

	// create output image to show results		// create output image to show results
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	Graphics2D g2 = output.createGraphics();		Graphics2D g2 = output.createGraphics();

	// Search for the cursor in the image. For demonstration purposes it has been pasted 3 times		// Search for the cursor in the image. For demonstration purposes it has been pasted 3 times
	g2.setColor(Color.RED); g2.setStroke(new BasicStroke(5));		g2.setColor(Color.RED);
			g2.setStroke(new BasicStroke(5));
	drawRectangles(g2, image, templateCursor, maskCursor, 3);		drawRectangles(g2, image, templateCursor, maskCursor, 3);
	// show match intensity image for this template		// show match intensity image for this template
	showMatchIntensity(image, templateCursor, maskCursor);		showMatchIntensity(image, templateCursor, maskCursor);

	// Now it's try finding the cursor without a mask. it will get confused when the background is black		// Now it's try finding the cursor without a mask. it will get confused when the background is black
	g2.setColor(Color.BLUE); g2.setStroke(new BasicStroke(2));		g2.setColor(Color.BLUE);
			g2.setStroke(new BasicStroke(2));
	drawRectangles(g2, image, templateCursor, null, 3);		drawRectangles(g2, image, templateCursor, null, 3);

	// Now it searches for a specific icon for which there is only one match		// Now it searches for a specific icon for which there is only one match
	g2.setColor(Color.ORANGE); g2.setStroke(new BasicStroke(3));		g2.setColor(Color.ORANGE);
			g2.setStroke(new BasicStroke(3));
	drawRectangles(g2, image, templatePaint, null, 1);		drawRectangles(g2, image, templatePaint, null, 1);

	ShowImages.showWindow(output, "Found Matches",true);		ShowImages.showWindow(output, "Found Matches", true);
	}		}

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	* Helper function will is finds matches and displays the results as colored rectangles		* Helper function will is finds matches and displays the results as colored rectangles
	*/		*/
	private static void drawRectangles(Graphics2D g2,		private static void drawRectangles( Graphics2D g2,
	GrayF32 image, GrayF32 template, GrayF32 mask,		GrayF32 image, GrayF32 template, GrayF32 mask,
	int expectedMatches) {		int expectedMatches ) {
	List<Match> found = findMatches(image, template, mask, expectedMatches);		List<Match> found = findMatches(image, template, mask, expectedMatches);

	int r = 2;		int r = 2;
	int w = template.width + 2 * r;		int w = template.width + 2*r;
	int h = template.height + 2 * r;		int h = template.height + 2*r;

	for (Match m : found) {		for (Match m : found) {
	System.out.printf("Match %3d %3d score = %6.2f\n",m.x,m.y,m.score);		System.out.printf("Match %3d %3d score = %6.2f\n", m.x, m.y, m.score);
	// this demonstrates how to filter out false positives		// this demonstrates how to filter out false positives
	// the meaning of score will depend on the template technique		// the meaning of score will depend on the template technique

Peter at 20:16, 21 December 2020

2020-12-21T20:16:33Z

← Older revision		Revision as of 20:16, 21 December 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.35/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	*/		*/
	public class ExampleTemplateMatching {		public class ExampleTemplateMatching {

	/**		/**
	* Demonstrates how to search for matches of a template inside an image		* Demonstrates how to search for matches of a template inside an image
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	*/		*/
	private static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {		private static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {

	// create algorithm for computing intensity image		// create algorithm for computing intensity image
	TemplateMatchingIntensity<GrayF32> matchIntensity =		TemplateMatchingIntensity<GrayF32> matchIntensity =
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	}		}

	public static void main(String ~~args~~[]) {		public static void main(String[] args) {

	// Load image and templates		// Load image and templates
	String directory = UtilIO.pathExample("template");		String directory = UtilIO.pathExample("template");

Peter at 00:59, 24 December 2019

2019-12-24T00:59:42Z

← Older revision		Revision as of 00:59, 24 December 2019
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.35/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	// create template matcher.		// create template matcher.
	TemplateMatching<GrayF32> matcher =		TemplateMatching<GrayF32> matcher =
	FactoryTemplateMatching.createMatcher(TemplateScoreType.~~SUM_DIFF_SQ~~, GrayF32.class);		FactoryTemplateMatching.createMatcher(TemplateScoreType.SUM_SQUARE_ERROR, GrayF32.class);

	// Find the points which match the template the best		// Find the points which match the template the best
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	return matcher.getResults().toList();		return matcher.getResults().toList();

	}		}

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	* a better match to the template.		* a better match to the template.
	*/		*/
	~~public~~ static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {		private static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {

	// create algorithm for computing intensity image		// create algorithm for computing intensity image
	TemplateMatchingIntensity<GrayF32> matchIntensity =		TemplateMatchingIntensity<GrayF32> matchIntensity =
	FactoryTemplateMatching.createIntensity(TemplateScoreType.~~SUM_DIFF_SQ~~, GrayF32.class);		FactoryTemplateMatching.createIntensity(TemplateScoreType.SUM_SQUARE_ERROR, GrayF32.class);

	// apply the template to the image		// apply the template to the image
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	GrayF32 intensity = matchIntensity.getIntensity();		GrayF32 intensity = matchIntensity.getIntensity();

	// ~~adjust the intensity image so that white indicates~~ a good match and black a ~~poor~~ match		// White will indicate a good match and black a bad match, or the reverse
	// the ~~scale is kept linear to highlight how ambiguous the solution is~~		// depending on the cost function used.
	float min = ImageStatistics.min(intensity);		float min = ImageStatistics.min(intensity);
	float max = ImageStatistics.max(intensity);		float max = ImageStatistics.max(intensity);
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	for (Match m : found) {		for (Match m : found) {
	System.out.~~println~~("Match "+m.x~~+" "+~~m.y~~+" score "+~~m.score);		System.out.printf("Match %3d %3d score = %6.2f\n",m.x,m.y,m.score);
	// this demonstrates how to filter out false positives		// this demonstrates how to filter out false positives
	// the meaning of score will depend on the template technique		// the meaning of score will depend on the template technique
	// if( m.score < -~~1000~~ ) // This line is commented out for demonstration purposes		// if( m.score < -5 ) // This line is commented out for demonstration purposes
	// continue;		// continue;

Peter at 22:40, 1 December 2016

2016-12-01T22:40:39Z

← Older revision		Revision as of 22:40, 1 December 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	// Find the points which match the template the best		// Find the points which match the template the best
			matcher.setImage(image);
	matcher.setTemplate(template, mask,expectedMatches);		matcher.setTemplate(template, mask,expectedMatches);
	matcher.process(~~image~~);		matcher.process();

	return matcher.getResults().toList();		return matcher.getResults().toList();
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	// apply the template to the image		// apply the template to the image
	matchIntensity.process(~~image,~~ template, mask);		matchIntensity.setInputImage(image);
			matchIntensity.process(template, mask);

	// get the results		// get the results
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	for (Match m : found) {		for (Match m : found) {
			System.out.println("Match "+m.x+" "+m.y+" score "+m.score);
			// this demonstrates how to filter out false positives
			// the meaning of score will depend on the template technique
			// if( m.score < -1000 ) // This line is commented out for demonstration purposes
			// continue;

	// the return point is the template's top left corner		// the return point is the template's top left corner
	int x0 = m.x - r;		int x0 = m.x - r;

Peter at 05:24, 28 March 2016

2016-03-28T05:24:54Z

← Older revision		Revision as of 05:24, 28 March 2016
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	* @return List of match location and scores		* @return List of match location and scores
	*/		*/
	private static List<Match> findMatches(~~ImageFloat32~~ image, ~~ImageFloat32~~ template, ~~ImageFloat32~~ mask,		private static List<Match> findMatches(GrayF32 image, GrayF32 template, GrayF32 mask,
	int expectedMatches) {		int expectedMatches) {
	// create template matcher.		// create template matcher.
	TemplateMatching<~~ImageFloat32~~> matcher =		TemplateMatching<GrayF32> matcher =
	FactoryTemplateMatching.createMatcher(TemplateScoreType.SUM_DIFF_SQ, ~~ImageFloat32~~.class);		FactoryTemplateMatching.createMatcher(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);

	// Find the points which match the template the best		// Find the points which match the template the best
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	* a better match to the template.		* a better match to the template.
	*/		*/
	public static void showMatchIntensity(~~ImageFloat32~~ image, ~~ImageFloat32~~ template, ~~ImageFloat32~~ mask) {		public static void showMatchIntensity(GrayF32 image, GrayF32 template, GrayF32 mask) {

	// create algorithm for computing intensity image		// create algorithm for computing intensity image
	TemplateMatchingIntensity<~~ImageFloat32~~> matchIntensity =		TemplateMatchingIntensity<GrayF32> matchIntensity =
	FactoryTemplateMatching.createIntensity(TemplateScoreType.SUM_DIFF_SQ, ~~ImageFloat32~~.class);		FactoryTemplateMatching.createIntensity(TemplateScoreType.SUM_DIFF_SQ, GrayF32.class);

	// apply the template to the image		// apply the template to the image
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	// get the results		// get the results
	~~ImageFloat32~~ intensity = matchIntensity.getIntensity();		GrayF32 intensity = matchIntensity.getIntensity();

	// adjust the intensity image so that white indicates a good match and black a poor match		// adjust the intensity image so that white indicates a good match and black a poor match
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	String directory = UtilIO.pathExample("template");		String directory = UtilIO.pathExample("template");

	~~ImageFloat32~~ image = UtilImageIO.loadImage(directory ,"desktop.png", ~~ImageFloat32~~.class);		GrayF32 image = UtilImageIO.loadImage(directory ,"desktop.png", GrayF32.class);
	~~ImageFloat32~~ templateCursor = UtilImageIO.loadImage(directory , "cursor.png", ~~ImageFloat32~~.class);		GrayF32 templateCursor = UtilImageIO.loadImage(directory , "cursor.png", GrayF32.class);
	~~ImageFloat32~~ maskCursor = UtilImageIO.loadImage(directory , "cursor_mask.png", ~~ImageFloat32~~.class);		GrayF32 maskCursor = UtilImageIO.loadImage(directory , "cursor_mask.png", GrayF32.class);
	~~ImageFloat32~~ templatePaint = UtilImageIO.loadImage(directory , "paint.png", ~~ImageFloat32~~.class);		GrayF32 templatePaint = UtilImageIO.loadImage(directory , "paint.png", GrayF32.class);

	// create output image to show results		// create output image to show results
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	*/		*/
	private static void drawRectangles(Graphics2D g2,		private static void drawRectangles(Graphics2D g2,
	~~ImageFloat32~~ image, ~~ImageFloat32~~ template, ~~ImageFloat32~~ mask,		GrayF32 image, GrayF32 template, GrayF32 mask,
	int expectedMatches) {		int expectedMatches) {
	List<Match> found = findMatches(image, template, mask, expectedMatches);		List<Match> found = findMatches(image, template, mask, expectedMatches);

Peter at 16:50, 9 November 2015

2015-11-09T16:50:31Z

← Older revision		Revision as of 16:50, 9 November 2015
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/features/ExampleTemplateMatching.java ExampleTemplateMatching.java]

	Concepts:		Concepts:
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	/**		/**
	* Example of how to find objects inside an image using template matching. Template matching works		* Example of how to find objects inside an image using template matching. Template matching works
	* well when there is little noise in the image and the object's appearance is known and static.		* well when there is little noise in the image and the object's appearance is known and static. It can
			* also be very slow to compute, depending on the image and template size.
	*		*
	* @author Peter Abeles		* @author Peter Abeles
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	* @param image Image being searched		* @param image Image being searched
	* @param template Template being looked for		* @param template Template being looked for
	* @param mask Mask which determines ~~influence~~ of each pixel in ~~template on~~ score		* @param mask Mask which determines the weight of each template pixel in the match score
	* @param expectedMatches Number of expected matches it hopes to find		* @param expectedMatches Number of expected matches it hopes to find
	* @return List of match location and scores		* @return List of match location and scores
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	BufferedImage output = new BufferedImage(image.width, image.height, BufferedImage.TYPE_INT_BGR);		BufferedImage output = new BufferedImage(image.width, image.height, BufferedImage.TYPE_INT_BGR);
	VisualizeImageData.grayMagnitude(intensity, output, -1);		VisualizeImageData.grayMagnitude(intensity, output, -1);
	ShowImages.showWindow(output, "Match Intensity");		ShowImages.showWindow(output, "Match Intensity", true);
	}		}

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	// Load image and templates		// Load image and templates
	String directory = "~~../data/applet/~~template/";		String directory = UtilIO.pathExample("template");

	ImageFloat32 image = UtilImageIO.loadImage(directory + "desktop.png", ImageFloat32.class);		ImageFloat32 image = UtilImageIO.loadImage(directory ,"desktop.png", ImageFloat32.class);
	ImageFloat32 templateCursor = UtilImageIO.loadImage(directory + "cursor.png", ImageFloat32.class);		ImageFloat32 templateCursor = UtilImageIO.loadImage(directory , "cursor.png", ImageFloat32.class);
	ImageFloat32 maskCursor = UtilImageIO.loadImage(directory + "cursor_mask.png", ImageFloat32.class);		ImageFloat32 maskCursor = UtilImageIO.loadImage(directory , "cursor_mask.png", ImageFloat32.class);
	ImageFloat32 templatePaint = UtilImageIO.loadImage(directory + "paint.png", ImageFloat32.class);		ImageFloat32 templatePaint = UtilImageIO.loadImage(directory , "paint.png", ImageFloat32.class);

	// create output image to show results		// create output image to show results

Peter at 13:32, 25 September 2015

2015-09-25T13:32:50Z

← Older revision		Revision as of 13:32, 25 September 2015
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	</center>		</center>

	Template matching ~~finds all~~ the ~~points inside an~~ image ~~which match a template~~. A ~~template~~ is ~~simply~~ a ~~smaller image~~ and ~~optionally~~ a ~~mask~~. Typically template matching is only used in highly controlled environments and doesn't work to well in natural scenes. ~~A template matching algorithm works by computing a fit score for each pixel in the image~~ and ~~then looking for local maximums~~.		Template matching compares a smaller image (the template) against every possible location in a larger target image. A match is declared the fit score is a local peak and above a threshold. Typically template matching is only used in highly controlled environments and doesn't work to well in natural scenes. It's also extremely computationally expensive and larger images/templates are likely to take an excessive amount of time to process.

	The example below is intended to demonstrate the strengths and weaknesses of template matching. For each template the number of matches returned needs to be specified. If the number of matches is known then the results are good in this example, but if too many are requested the some of the results are noise. The intensity image is shown for a match. Notice how ambiguous the results are.		The example below is intended to demonstrate the strengths and weaknesses of template matching. For each template the number of matches returned needs to be specified. If the number of matches is known then the results are good in this example, but if too many are requested the some of the results are noise. The intensity image is shown for a match. Notice how ambiguous the results are.

Peter at 13:00, 16 September 2015

2015-09-16T13:00:50Z

← Older revision		Revision as of 13:00, 16 September 2015
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	<center>		<center>
	<gallery widths=250px heights=200px>		<gallery widths=250px heights=200px>
	File:Example_template_matches.jpg \| Found matches for ~~three different templates~~.		File:Example_template_matches.jpg \| Found matches for the cursor with and without a mask.
	File:Example_template_intensity.jpg \| Match intensity for a template.		File:Example_template_intensity.jpg \| Match intensity for a template.
	</gallery>		</gallery>