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Introduction

This API lets you recognize a barcode from file on the server with parameters in the request body.

Resource URI

Please use Aspose.BarCode for Cloud APIs' Swagger UI to call PUT /barcode/{name}/recognize REST API directly from the browser. The description of important API parameters and their valid values are given below.

BarcodeReader object parameters are below:

Parameter name

Possible values

Description

ChecksumValidation

Default, On, Off

Sets mode for checksum validation during recognition.

StripFNC

True, False

Sets if FNC symbol stripping should be performed.

RecognitionMode

MaxPerformance, MaxBarcodes, MaxQuality

Sets recognition mode.

ManualHints

None, InvertImage, IncorrectBarcodes, ComplexBackground

Sets preprocessing of an image.

Parameter

Valid values

Description

name

upce-20.jpg

Filename of image.

type

type=upce

If this parameter is empty, autodetection of all supported types is used.

cURL Example

 Request
 Response

SDKs

Using an SDK (API client) is the quickest way for a developer to speed up the development. An SDK takes care of a lot of low-level details of making requests and handling responses and lets you focus on writing code specific to your particular project. Checkout our GitHub repository for a complete list of Aspose.BarCode SDKs along with working examples, to get you started in no time.

 SDK Examples

Read Barcode from Local Image

 C#
 Java
 PHP
 Ruby
 Python
 Node.js
 Android
 Objective C
 Perl

Read Barcode from External Image URL

 C#
 Java
 PHP
 Ruby
 Python
 Node.js
 Android
 Objective C
 Perl

Read Barcode from Request Body

Read Barcode from Request body. Request body can contain raw data bytes of the image or encoded with base64
 C#
 PHP
 Ruby
 Node.js
 Perl
 Objective C

Recognise Barcode with Checksum Option

 C#
 Java
 PHP
 Ruby
 Python
 Node.js
 Android
 Objective C
 Perl

Read Barcodes by Applying Image Processing Algorithm

 Aspose.BarCode for Cloud provides better and faster barcode recognition with the following image processing algorithms:
  • Complex background
    RecognitionHints.ImageBinarizationHints.ComplexBackground
    This technique can locate a barcode region in complex or colored background through region-based image analysis.
  • Grayscale image processing
    RecognitionHints.ImageBinarizationHints.Grayscale
    This techniques converts the image to grayscale. This can be useful when detecting bar codes from scanned or slightly damaged images. The probability of bar code detection increases with this setting.
  • Invert image
  • RecognitionHints.ImageBinarizationHints.InvertImage
    This technique inverts the image before recognition. It helps the code to recognize images with a black background and white, or near, barcode.
  • Median smoothing image processing
    RecognitionHints.ImageBinarizationHints.MedianSmoothing
    Median smoothing removes the noise from the image while preserving the image edges. This technique gives a perfect result. In more complicated images, less data is lost by taking the median.
  • MedianSmoothingWindowSize: Gets or sets the median smoothing window size. Typical values are 3 or 4. The default value is 3. The recognition hint {{MedianSmoothing}} must be set. For noisy images, 4 is good value.

 

 C#
 Java
 PHP
 Ruby
 Python
 Node.js
 Android
 Objective C
 Perl

 

 

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