Halftone Removal

The 'Maximum Speck Size' property defines the largest area (in display units) for a dot to be considered part of a halftone pattern.

• Specks larger than this value will not be included in halftone detection.
• Specify the value in units such as pt, px, or mm.
• Review the "Specks" diagnostic image to ensure all relevant dots are detected.

Example

To detect only very small dots, set this property to 1pt or 2px.

Can be one of the following values:

The 'Speck Connectivity' property determines how pixels are considered "connected" when grouping them into specks.

• Choose between 4-way or 8-way connectivity, depending on whether diagonal connections should be included.
• 4-way connectivity considers only horizontal and vertical neighbors, while 8-way includes diagonals.
• The choice affects which pixels are grouped as a single speck and can impact detection accuracy.

Example

Use 8-way connectivity to group diagonally touching pixels into a single speck, which is useful for irregular dot shapes.

The 'Minimum Region Area' property sets the smallest total area (in square display units) for a region to be classified as halftone.

• Only regions with an area equal to or greater than this value will be removed.
• Specify the value in units such as pt², px², or mm².
• Review the "Candidates" and "Regions" diagnostic images to ensure correct region selection.

Example

To remove only large halftone regions, set this property to 9pt or higher.

The 'Minimum Region Size' property sets the smallest dimension (in display units) for a region to be considered halftone.

• Only regions with both width and height equal to or greater than this value will be removed.
• Specify the value in units such as pt, px, or mm.
• Use this property to avoid removing small, non-halftone features.

Example

To remove only regions at least 5 points wide and tall, set this property to 5pt.

The 'Maximum Spacing' property controls how far apart specks can be and still be grouped into a single halftone region.

• Increase this value to join more distant specks into larger regions.
• Decrease to restrict grouping to tightly clustered dots.
• Specify the value in units such as pt, px, or mm.
• Review the "Candidates" diagnostic image to tune this property.

Example

To group only closely spaced dots, set this property to 2pt or less.

Can be one of the following types:

The 'Dropout Method' property determines the technique used to remove or replace regions of the image identified by the feature mask. This allows you to control the visual result of the dropout operation, depending on your processing goals.

Common dropout methods include:

• Filling masked regions with a solid color (such as white or the detected background color).
• Replacing masked regions with interpolated content from surrounding pixels.
• Applying custom fill logic as defined by the selected Dropout Method.

Choosing the appropriate dropout method is important for maintaining the readability and appearance of the processed image. For example, filling with white may be suitable for removing background noise, while interpolation may be preferred when removing lines or halftones from text regions.

Example: To remove halftone patterns and fill the resulting regions with the detected background color, select the 'Background Fill' option from the 'Dropout Method' dropdown.

Review the diagnostic images generated in diagnostic mode to verify that the selected method produces the desired effect on your sample images.

The 'Binarization Settings' property determines the thresholding method and parameters used to create the binarized image that serves as the basis for feature detection in Binary Dropout commands.

Binarization is a critical preprocessing step: it transforms the input image into an 8-bit black and white version, making features such as barcodes, halftones, or lines more distinct and easier to detect.

Configuration Guidance

• Select the thresholding method using the 'Method' property within 'Binarization Settings'.
• Adjust additional parameters such as threshold value, window size, kernel type, and adjustment as needed for your document type.
• For most standard documents, 'Auto' or 'Adaptive' methods provide the best results.
• For documents with variable backgrounds or lighting, use 'Adaptive' or 'Dynamic' and tune the window size and kernel type.

Notes

• The quality of the binarized image directly affects the accuracy of feature detection and dropout.
• Review the diagnostic output to ensure that the features you wish to remove are clearly visible in the binarized image.

The 'Command Type Name' property shows the user-friendly name of the IP Command as it appears in the Grooper UI. This helps users identify which command is being configured or executed, especially when working with IP Profiles containing multiple commands.

This property is read-only and is automatically set based on the command's type.

The 'Supported Pixel Formats' property lists the image pixel formats that the IP Command can process. If an image does not match one of these formats, the command will be skipped for that image.

• By default, all pixel formats are supported unless a derived command restricts this list.
• Example formats include Pixel8bppGrayscale, Pixel24bppBgr, and Pixel1bppIndexed.

Use this property to verify compatibility when building IP Profiles or troubleshooting why a command did not execute.