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DeblurModes

Parameter DeblurModes defines the mode and priority for deblurring.

JSON Structure

Location in template:

BarcodeReaderTaskSettingOptions[i]
    ├── SectionArray[j]
    │   └── StageArray[k] (Stage object)
    │       └── DeblurModes

Parent object: DecodeBarcodesStage object

Example:

{
    "DeblurModes": [
        {
            "Mode": "DM_BASED_ON_LOC_BIN"
        },
        {
            "Mode": "DM_THRESHOLD_BINARIZATION" 
        }
    ]
}

This snippet shows only the DeblurModes parameter.

To use it, embed this parameter within a Stage object at the SST_DECODE_BARCODES stage.

For the complete JSON structure, see:

Full JSON Structure

Minimal Valid JSON

Parameter Details

Parameter DeblurModes consists of a group of deblur mode objects. Each deblur mode object includes a candidate mode and a series of auxiliary mode arguments.

Mode Arguments

The mode arguments of the deblur mode object are shown as follows:

Mode Argument Name	Mode Argument Summary
Mode (Required)	Description Specifies a deblur mode.
	Type String
	Candidate Mode List DM_DIRECT_BINARIZATION DM_THRESHOLD_BINARIZATION DM_GRAY_EQUALIZATION DM_SMOOTHING DM_MORPHING DM_DEEP_ANALYSIS DM_SHARPENING DM_BASED_ON_LOC_BIN DM_SHARPENING_SMOOTHING DM_NEURAL_NETWORK DM_SKIP
DeblurModelNameArray (Optional)	Description Sets the Convolutional Neural Networks (CNN) model files used for barcode decoding. It references the names of CaptureVisionModel objects.
	Type String Array
	Range Each element is the name of a `CaptureVisionModel` object.
	Default Value null
	Valid For DM_NEURAL_NETWORK.
	Remarks Deprecated in version 11.2.1000 and will be removed in future versions. Please use `ModelNameArray` instead.
ModelNameArray (Optional)	Description Sets the Convolutional Neural Networks (CNN) model files used for barcode decoding. It references the names of CaptureVisionModel objects.
	Type String Array
	Range Each element is the name of a `CaptureVisionModel` object. Candidate values: "OneDDeblur", "EAN13Decoder", "Code128Decoder".
	Default Value null
	Valid For DM_NEURAL_NETWORK.
	Remarks Introduced in version 11.2.1000. When set to null, all "OneDDeblur", "EAN13Decoder", "Code128Decoder" models will be used by default.
Level (Optional)	Description Sets the effort level used for deblurring, a larger value may improve the Read Rate but slowdown the Speed.
	Type int
	Range [1, 9]
	Default Value 4
	Valid For DM_NEURAL_NETWORK.
Methods (Optional)	Description Sets the methods used for deep analysis.
	Type String Array
	Range Each element is a deep analysis method. OneDGeneral: for OneD barcodes. TwoDGeneral: for 2D barcodes. EAN13Enhanced: for EAN13 barcodes.
	Default Value null
	Valid For DM_DEEP_ANALYSIS.
	Remarks Introduced in version 11.2.1000.

Default Setting

By default, deblur modes are not configured and set to null.

{
    "DeblurModes": null
}

Remarks:

When DeblurModes is null, the actual deblur modes used depend on the barcode format:

For PDF417 format:
[DM_BASED_ON_LOC_BIN, DM_THRESHOLD_BINARIZATION, DM_DIRECT_BINARIZATION, DM_SMOOTHING, DM_GRAY_EQUALIZATION, DM_MORPHING, DM_DEEP_ANALYSIS]
For OneD formats:
[DM_BASED_ON_LOC_BIN, DM_THRESHOLD_BINARIZATION, DM_DIRECT_BINARIZATION, DM_NEURAL_NETWORK (with EAN13Decoder and Code128Decoder), DM_DEEP_ANALYSIS, DM_SMOOTHING, DM_GRAY_EQUALIZATION, DM_MORPHING]
For other formats

[DM_BASED_ON_LOC_BIN,DM_THRESHOLD_BINARIZATION,DM_DIRECT_BINARIZATION,DM_DEEP_ANALYSIS,DM_SMOOTHING,DM_GRAY_EQUALIZATION,DM_MORPHING]

Candidate Mode Introductions

DM_DIRECT_BINARIZATION

Performs deblur process using the binarization algorithm. This mode has the following arguments for further customizing.

DM_THRESHOLD_BINARIZATION

Performs deblur process using the threshold binarization algorithm.

When processing OneD barcodes, you can add two DM_THRESHOLD_BINARIZATION to your DeblurModes settings. If you do, the second round DM_THRESHOLD_BINARIZATION will detect and fill in the blurry area with predicted barcode modules. The second round DM_THRESHOLD_BINARIZATION can sharpenly improve the read-rate of blurry OneD barcodes but sacrifice the accuracy.

This mode has the following arguments for further customizing.

DM_GRAY_EQUALIZATION

Performs deblur process using the gray equalization algorithm. This mode has the following arguments for further customizing.

DM_SMOOTHING

Performs deblur process using the smoothing algorithm. This mode has the following arguments for further customizing.

DM_MORPHING

Performs deblur process using the morphing algorithm. This mode has the following arguments for further customizing.

DM_DEEP_ANALYSIS

Performs deblur process using the deep analysis algorithm. This mode has the following arguments for further customizing.

Available Mode Arguments:

Methods

DM_SHARPENING

Performs deblur process using the sharpening algorithm. This mode has the following arguments for further customizing.

DM_BASED_ON_LOC_BIN

Performs deblur process based on the binary image from the localization process. This mode has the following arguments for further customizing.

DM_SHARPENING_SMOOTHING

Performs deblur process using the sharpening and smoothing algorithm. This mode has the following arguments for further customizing.

DM_NEURAL_NETWORK

Performs deblur process by utilizing a neural network model.

Available Mode Arguments:

ModelNameArray
Level