MaskingResult.Length

MaskingResult.Length property

Gets the length.

public int Length { get; }

Property Value

The length.

Examples

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.

[C#]

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

using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Blue hills.png"))
{
    Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();

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

    // Set the maximum number of iterations.
    args.MaxIterationNumber = 50;

    // Set the precision of segmentation method (optional)
    args.Precision = 1;
        
    // Each cluster (segment) will be stored to a separate PNG file.
    Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
    exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
    exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());

    Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();

    // Use K-means clustering.
    // K-means clustering allows to split image into several independent clusters (segments).
    maskingOptions.Method = Masking.Options.SegmentationMethod.KMeans;
    maskingOptions.Decompose = true;
    maskingOptions.Args = args;
        
    // The backgroung color will be orange.
    maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
    maskingOptions.ExportOptions = exportOptions;

    // Create an instance of the ImageMasking class.
    Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResult.Length; i++)
        {
            string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
            using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
            {
                resultImage.Save(dir + outputFileName);
            }
        }
    }
}

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

[C#]

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

// Define a manual mask.
Aspose.Imaging.GraphicsPath manualMask = new Aspose.Imaging.GraphicsPath();
Aspose.Imaging.Figure figure = new Aspose.Imaging.Figure();
figure.AddShape(new Aspose.Imaging.Shapes.EllipseShape(new RectangleF(50, 50, 40, 40)));
figure.AddShape(new Aspose.Imaging.Shapes.RectangleShape(new RectangleF(10, 20, 50, 30)));
manualMask.AddFigure(figure);

// Each cluster (segment) will be stored to a separate PNG file.
Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());

// Set the manual mask.
Aspose.Imaging.Masking.Options.ManualMaskingArgs args = new Aspose.Imaging.Masking.Options.ManualMaskingArgs();
args.Mask = manualMask;

using (RasterImage image = (RasterImage)Image.Load(dir + "Blue hills.png"))
{
    Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();

    // Use manual clustering algorithm.
    maskingOptions.Method = Masking.Options.SegmentationMethod.Manual;

    // All shapes making up a mask will be combined into one. 
    maskingOptions.Decompose = false;
    maskingOptions.Args = args;

    // The backgroung color will be orange.
    maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
    maskingOptions.ExportOptions = exportOptions;

    // The area of the source image that masking will be applied to.
    maskingOptions.MaskingArea = new Rectangle(50, 50, 120, 120);

    // Create an instance of the ImageMasking class.
    Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResult.Length; i++)
        {
            string outputFileName = string.Format("Blue hills.Segment{0}.png", maskingResult[i].ObjectNumber);
            using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
            {
                resultImage.Save(dir + outputFileName);
            }
        }
    }
}

This example shows how to specify suggestions for image masking algorithm to improve precision of segmentation (clustering) method. Image masking is an image processing technique that is used to split the background from the foreground image objects.

[C#]

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

using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
    Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();

    // Suggestion #1.
    // Analyze the image visually and set the area of interest. The result of segmentation will include only objects that will be completely located within this area.
    args.ObjectsRectangles = new Rectangle[]
    {
        new Rectangle(86, 6, 270, 364),
    };

    // Suggestion #2.
    // Analyze the image visually and set the points that belong to separated objects.
    args.ObjectsPoints = new Point[][]
    {
        new Point[] { new Point(103, 326) },
        new Point[] { new Point(280, 43) },
        new Point[] { new Point(319, 86) },
    };

    // Each cluster (segment) will be stored to a separate PNG file.
    Aspose.Imaging.ImageOptions.PngOptions exportOptions = new Aspose.Imaging.ImageOptions.PngOptions();
    exportOptions.ColorType = Aspose.Imaging.FileFormats.Png.PngColorType.TruecolorWithAlpha;
    exportOptions.Source = new Aspose.Imaging.Sources.StreamSource(new System.IO.MemoryStream());

    Aspose.Imaging.Masking.Options.MaskingOptions maskingOptions = new Aspose.Imaging.Masking.Options.MaskingOptions();
        
    // Use GraphCut clustering.
    maskingOptions.Method = Masking.Options.SegmentationMethod.GraphCut;
    maskingOptions.Decompose = false;
    maskingOptions.Args = args;

    // The backgroung color will be orange.
    maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
    maskingOptions.ExportOptions = exportOptions;

    // Create an instance of the ImageMasking class.
    Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);

    // Divide the source image into several clusters (segments).
    using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = masking.Decompose(maskingOptions))
    {
        // Obtain images from masking result and save them to PNG.
        for (int i = 0; i < maskingResult.Length; i++)
        {
            string outputFileName = string.Format("Gorilla.Segment{0}.png", maskingResult[i].ObjectNumber);
            using (Aspose.Imaging.Image resultImage = maskingResult[i].GetImage())
            {
                resultImage.Save(dir + outputFileName);
            }
        }
    }
}

MaskingResult.Length