Class AutoMaskingArgs
Class AutoMaskingArgs
Namespace: Aspose.Imaging.Masking.Options
Assembly: Aspose.Imaging.dll (25.2.0)
Represents the arguments that are specified for automated masking methods
public class AutoMaskingArgs : IMaskingArgsInheritance
Implements
Inherited Members
object.GetType(), object.MemberwiseClone(), object.ToString(), object.Equals(object?), object.Equals(object?, object?), object.ReferenceEquals(object?, object?), object.GetHashCode()
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.```csharp [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);
}
}
}
}
Using a segment mask to speed up the segmentation process```csharp
[C#]
// Masking export options
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 = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// The backgroung color will be transparent.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Transparent;
maskingOptions.ExportOptions = exportOptions;
string dir = "c:\\temp\\";
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "BigImage.jpg"))
{
Aspose.Imaging.Size imageSize = image.Size;
// Reducing image size to speed up the segmentation process
image.ResizeHeightProportionally(600, Aspose.Imaging.ResizeType.HighQualityResample);
// 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))
{
// Getting the foreground mask
using (Aspose.Imaging.RasterImage foregroundMask = maskingResult[1].GetMask())
{
// Increase the size of the mask to the size of the original image
foregroundMask.Resize(imageSize.Width, imageSize.Height, Aspose.Imaging.ResizeType.NearestNeighbourResample);
// Applying the mask to the original image to obtain a foreground segment
using (Aspose.Imaging.RasterImage originImage = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "BigImage.jpg"))
{
Aspose.Imaging.Masking.ImageMasking.ApplyMask(originImage, foregroundMask, maskingOptions);
originImage.Save(dir + "BigImage_foreground.png", exportOptions);
}
}
}
}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.```csharp [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);
}
}
}
}
Saving the masking session to a file for long sessions, as well as for the possibility of resuming the session in another environment.```csharp
[C#]
string dir = "c:\\temp\\";
string sessionBackupFile = dir + "session.bak";
// Masking export options
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 = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// The backgroung color will be orange.
maskingOptions.BackgroundReplacementColor = Aspose.Imaging.Color.Orange;
maskingOptions.ExportOptions = exportOptions;
// Starting a session for the first time and saving to a file
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
using (Aspose.Imaging.Masking.IMaskingSession session = masking.CreateSession(maskingOptions))
{
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = session.Decompose())
{
using (Aspose.Imaging.RasterImage segmentImage = maskingResult[1].GetImage())
{
segmentImage.Save(dir + "step1.png");
}
}
session.Save(sessionBackupFile);
}
}
// Resuming a masking session from a file
using (Aspose.Imaging.RasterImage image = (Aspose.Imaging.RasterImage)Aspose.Imaging.Image.Load(dir + "Gorilla.bmp"))
{
// Create an instance of the ImageMasking class.
Aspose.Imaging.Masking.ImageMasking masking = new Aspose.Imaging.Masking.ImageMasking(image);
using (Aspose.Imaging.Masking.IMaskingSession session = masking.LoadSession(sessionBackupFile))
{
Aspose.Imaging.Masking.Options.AutoMaskingArgs args = new Aspose.Imaging.Masking.Options.AutoMaskingArgs();
// Analyze the image visually and set the points that belong to separated objects.
args.ObjectsPoints = new Point[][]
{
new Point[]
{
new Point(0, 0), new Point(0, 1), new Point(1, 0),
new Point(1, 1), new Point(2, 0), new Point(2, 1),
new Point(3, 0), new Point(3, 1)
},
};
using (Aspose.Imaging.Masking.Result.MaskingResult maskingResult = session.ImproveDecomposition(args))
{
// Explicit transfer of export options, since it is not serializable
maskingResult.MaskingOptions.ExportOptions = exportOptions;
using (Aspose.Imaging.RasterImage segmentImage = maskingResult[1].GetImage())
{
segmentImage.Save(dir + "step2.png");
}
}
}
}Constructors
AutoMaskingArgs()
public AutoMaskingArgs()Properties
MaxIterationNumber
Gets or sets the maximum number of iterations.
public int MaxIterationNumber { get; set; }Property Value
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.```csharp [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);
}
}
}
}
### <a id="Aspose_Imaging_Masking_Options_AutoMaskingArgs_NumberOfObjects"></a> NumberOfObjects
Gets or sets the number of objects
to separate initial image to (optional), default value is 2 (object and background).
```csharp
public int NumberOfObjects { get; set; }Property Value
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.```csharp [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);
}
}
}
}
### <a id="Aspose_Imaging_Masking_Options_AutoMaskingArgs_ObjectsPoints"></a> ObjectsPoints
Gets or sets the points that belong to separated objects (optional)
NumberOfObjects coordinates that belong to NumberOfObjects objects of initial image.
This parameter is used to increase segmentation method precision.
```csharp
public Point[][] ObjectsPoints { get; set; }Property Value
Point[][]
Examples
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.```csharp [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);
}
}
}
}
### <a id="Aspose_Imaging_Masking_Options_AutoMaskingArgs_ObjectsRectangles"></a> ObjectsRectangles
Gets or sets the objects rectangles that belong to separated objects (optional).
This parameter is used to increase segmentation method precision.
```csharp
public Rectangle[] ObjectsRectangles { get; set; }Property Value
Examples
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.```csharp [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);
}
}
}
}
### <a id="Aspose_Imaging_Masking_Options_AutoMaskingArgs_OrphanedPoints"></a> OrphanedPoints
Gets or sets the points that no longer belong to any object (optional).
This parameter is used only in case of re-segmentation.
```csharp
public Point[] OrphanedPoints { get; set; }Property Value
Point[]
Precision
Gets or sets the precision of segmentation method (optional).
public double Precision { get; set; }Property Value
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.```csharp [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);
}
}
}
}
## See Also
[IMaskingArgs](/imaging/aspose.imaging.masking.options.imaskingargs)