com.aspose.imaging.masking.result

Interface IMaskingLayer

public interface IMaskingLayer

Masking layer

Code example:

This example shows how to decompose a raster image into multiple images using image masking and the K-means segmentation algorithm. Image masking is an image processing technique that is used to split the background from the foreground image objects.

String dir = "c:\\temp\\";

com.aspose.imaging.RasterImage image = (com.aspose.imaging.RasterImage) com.aspose.imaging.Image.load(dir + "Blue hills.png");
try {
    com.aspose.imaging.masking.options.AutoMaskingArgs args = new com.aspose.imaging.masking.options.AutoMaskingArgs();

    // Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
    args.setNumberOfObjects(3);

    // Set the maximum number of iterations.
    args.setMaxIterationNumber(50);

    // Set the precision of segmentation method (optional)
    args.setPrecision(1);

    // Each cluster (segment) will be stored to a separate PNG file.
    com.aspose.imaging.imageoptions.PngOptions exportOptions = new com.aspose.imaging.imageoptions.PngOptions();
    exportOptions.setColorType(com.aspose.imaging.fileformats.png.PngColorType.TruecolorWithAlpha);
    exportOptions.setSource(new com.aspose.imaging.sources.StreamSource(new java.io.ByteArrayInputStream(new byte[0])));

    com.aspose.imaging.masking.options.MaskingOptions maskingOptions = new com.aspose.imaging.masking.options.MaskingOptions();

    // Use K-means clustering.
    // K-means clustering allows to split image into several independent clusters (segments).
    maskingOptions.setMethod(com.aspose.imaging.masking.options.SegmentationMethod.KMeans);
    maskingOptions.setDecompose(true);
    maskingOptions.setArgs(args);

    // The backgroung color will be orange.
    maskingOptions.setBackgroundReplacementColor(com.aspose.imaging.Color.getOrange());
    maskingOptions.setExportOptions(exportOptions);

    // Create an instance of the ImageMasking class.
    com.aspose.imaging.masking.ImageMasking masking = new com.aspose.imaging.masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    com.aspose.imaging.masking.result.MaskingResult maskingResults = masking.decompose(maskingOptions);
    try
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResults.getLength(); i++) {
            final IMaskingLayer resultsItem = maskingResults.get_Item(i);
            String outputFileName = String.format("Blue hills.Segment%s.png", resultsItem.getObjectNumber());
            Image resultImage = resultsItem.getImage();
            try {
                resultImage.save(dir + outputFileName);
            } finally {
                resultImage.close();
            }
        }
    }
    finally
    {
        maskingResults.close();
    }
} finally {
    image.close();
}

Method Summary

Modifier and Type	Method and Description
RasterImage	getImage() Provides result image.
RasterImage	getMask() Gets the image mask.
int	getObjectNumber() Gets the object number.

Method Detail

getObjectNumber

int getObjectNumber()

Gets the object number.

Code example:

This example shows how to decompose a raster image into multiple images using image masking and the K-means segmentation algorithm. Image masking is an image processing technique that is used to split the background from the foreground image objects.

String dir = "c:\\temp\\";

com.aspose.imaging.RasterImage image = (com.aspose.imaging.RasterImage) com.aspose.imaging.Image.load(dir + "Blue hills.png");
try {
    com.aspose.imaging.masking.options.AutoMaskingArgs args = new com.aspose.imaging.masking.options.AutoMaskingArgs();

    // Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
    args.setNumberOfObjects(3);

    // Set the maximum number of iterations.
    args.setMaxIterationNumber(50);

    // Set the precision of segmentation method (optional)
    args.setPrecision(1);

    // Each cluster (segment) will be stored to a separate PNG file.
    com.aspose.imaging.imageoptions.PngOptions exportOptions = new com.aspose.imaging.imageoptions.PngOptions();
    exportOptions.setColorType(com.aspose.imaging.fileformats.png.PngColorType.TruecolorWithAlpha);
    exportOptions.setSource(new com.aspose.imaging.sources.StreamSource(new java.io.ByteArrayInputStream(new byte[0])));

    com.aspose.imaging.masking.options.MaskingOptions maskingOptions = new com.aspose.imaging.masking.options.MaskingOptions();

    // Use K-means clustering.
    // K-means clustering allows to split image into several independent clusters (segments).
    maskingOptions.setMethod(com.aspose.imaging.masking.options.SegmentationMethod.KMeans);
    maskingOptions.setDecompose(true);
    maskingOptions.setArgs(args);

    // The backgroung color will be orange.
    maskingOptions.setBackgroundReplacementColor(com.aspose.imaging.Color.getOrange());
    maskingOptions.setExportOptions(exportOptions);

    // Create an instance of the ImageMasking class.
    com.aspose.imaging.masking.ImageMasking masking = new com.aspose.imaging.masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    com.aspose.imaging.masking.result.MaskingResult maskingResults = masking.decompose(maskingOptions);
    try
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResults.getLength(); i++) {
            final IMaskingLayer resultsItem = maskingResults.get_Item(i);
            String outputFileName = String.format("Blue hills.Segment%s.png", resultsItem.getObjectNumber());
            Image resultImage = resultsItem.getImage();
            try {
                resultImage.save(dir + outputFileName);
            } finally {
                resultImage.close();
            }
        }
    }
    finally
    {
        maskingResults.close();
    }
} finally {
    image.close();
}

getImage

RasterImage getImage()

Provides result image.

Returns:

Result image.

Code example:

This example shows how to decompose a raster image into multiple images using image masking and the K-means segmentation algorithm. Image masking is an image processing technique that is used to split the background from the foreground image objects.

String dir = "c:\\temp\\";

com.aspose.imaging.RasterImage image = (com.aspose.imaging.RasterImage) com.aspose.imaging.Image.load(dir + "Blue hills.png");
try {
    com.aspose.imaging.masking.options.AutoMaskingArgs args = new com.aspose.imaging.masking.options.AutoMaskingArgs();

    // Set the number of clusters (separated objects). The default value is 2, the foreground object and the background.
    args.setNumberOfObjects(3);

    // Set the maximum number of iterations.
    args.setMaxIterationNumber(50);

    // Set the precision of segmentation method (optional)
    args.setPrecision(1);

    // Each cluster (segment) will be stored to a separate PNG file.
    com.aspose.imaging.imageoptions.PngOptions exportOptions = new com.aspose.imaging.imageoptions.PngOptions();
    exportOptions.setColorType(com.aspose.imaging.fileformats.png.PngColorType.TruecolorWithAlpha);
    exportOptions.setSource(new com.aspose.imaging.sources.StreamSource(new java.io.ByteArrayInputStream(new byte[0])));

    com.aspose.imaging.masking.options.MaskingOptions maskingOptions = new com.aspose.imaging.masking.options.MaskingOptions();

    // Use K-means clustering.
    // K-means clustering allows to split image into several independent clusters (segments).
    maskingOptions.setMethod(com.aspose.imaging.masking.options.SegmentationMethod.KMeans);
    maskingOptions.setDecompose(true);
    maskingOptions.setArgs(args);

    // The backgroung color will be orange.
    maskingOptions.setBackgroundReplacementColor(com.aspose.imaging.Color.getOrange());
    maskingOptions.setExportOptions(exportOptions);

    // Create an instance of the ImageMasking class.
    com.aspose.imaging.masking.ImageMasking masking = new com.aspose.imaging.masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    com.aspose.imaging.masking.result.MaskingResult maskingResults = masking.decompose(maskingOptions);
    try
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResults.getLength(); i++) {
            final IMaskingLayer resultsItem = maskingResults.get_Item(i);
            String outputFileName = String.format("Blue hills.Segment%s.png", resultsItem.getObjectNumber());
            Image resultImage = resultsItem.getImage();
            try {
                resultImage.save(dir + outputFileName);
            } finally {
                resultImage.close();
            }
        }
    }
    finally
    {
        maskingResults.close();
    }
} finally {
    image.close();
}

getMask

RasterImage getMask()

Gets the image mask.

Returns:

Result image mask.

Code example:

Using a segment mask to speed up the segmentation process

// Masking export options
com.aspose.imaging.imageoptions.PngOptions exportOptions = new com.aspose.imaging.imageoptions.PngOptions();
exportOptions.setColorType(com.aspose.imaging.fileformats.png.PngColorType.TruecolorWithAlpha);
exportOptions.setSource(new com.aspose.imaging.sources.StreamSource());

com.aspose.imaging.masking.options.MaskingOptions maskingOptions = new com.aspose.imaging.masking.options.MaskingOptions();

// Use GraphCut clustering.
maskingOptions.setMethod(com.aspose.imaging.masking.options.SegmentationMethod.GraphCut);
maskingOptions.setDecompose(false);
maskingOptions.setArgs(new com.aspose.imaging.masking.options.AutoMaskingArgs());

// The background color will be transparent.
maskingOptions.setBackgroundReplacementColor(com.aspose.imaging.Color.getTransparent());
maskingOptions.setExportOptions(exportOptions);

String dir = "c:\\temp\\";
com.aspose.imaging.RasterImage image = (com.aspose.imaging.RasterImage)com.aspose.imaging.Image.load(dir + "BigImage.jpg");
try
{
    com.aspose.imaging.Size imageSize = image.getSize();

    // Reducing image size to speed up the segmentation process
    image.resizeHeightProportionally(600, com.aspose.imaging.ResizeType.HighQualityResample);

    // Create an instance of the ImageMasking class.
    com.aspose.imaging.masking.ImageMasking masking = new com.aspose.imaging.masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    com.aspose.imaging.masking.result.MaskingResult maskingResult = masking.decompose(maskingOptions);
    try
    {
        // Getting the foreground mask
        com.aspose.imaging.RasterImage foregroundMask = maskingResult.get_Item(1).getMask();
        try
        {
            // Increase the size of the mask to the size of the original image
            foregroundMask.resize(imageSize.getWidth(), imageSize.getHeight(), com.aspose.imaging.ResizeType.NearestNeighbourResample);

            // Applying the mask to the original image to obtain a foreground segment
            com.aspose.imaging.RasterImage originImage = (com.aspose.imaging.RasterImage)com.aspose.imaging.Image.load(dir + "BigImage.jpg");
            try
            {
                com.aspose.imaging.masking.ImageMasking.applyMask(originImage, foregroundMask, maskingOptions);
                originImage.save(dir + "BigImage_foreground.png", exportOptions);
            }
            finally
            {
                originImage.close();
            }
        }
        finally
        {
            foregroundMask.close();
        }
    }
    finally
    {
        maskingResult.close();
    }
}
finally
{
    image.close();
}