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Process Receipt

Processes a receipt image to extract transaction information using ABBYY Cloud OCR service.

Common Properties​

  • Name - The custom name of the node.
  • Color - The custom color of the node.
  • Delay Before (sec) - Waits in seconds before executing the node.
  • Delay After (sec) - Waits in seconds after executing node.
  • Continue On Error - Automation will continue regardless of any error. The default value is false.

Inputs​

  • Image Path - Path to the receipt image file to be processed.

Options​

  • Country - Country format for receipt parsing (default: usa). Options include UK, USA, Australia, Canada, Japan, Germany, Italy, France, Brazil, Russia, China, Korea, Netherlands, Spain, Singapore, Taiwan, Turkey, Poland.
  • Image Source - Source of the image (default: auto). Options:
    • Auto - Automatically detect source
    • Photo - Image from camera or smartphone
    • Scanner - Image from flatbed scanner
  • Field Region Export Mode - How to export field regions (default: not set). Options:
    • Don't Export - Exclude field region data
    • For Original Image - Export regions for original image
    • For Corrected Image - Export regions for corrected image
  • Description - Optional description for the processing task.
  • PDF Password - Password for encrypted PDF files if applicable.
  • Correct Orientation - Automatically correct receipt orientation (default: false).
  • Correct Skew - Automatically correct receipt skew (default: false).
  • Write Extended Character Info - Include extended character information (default: false).

Outputs​

  • Task - ABBYY task object containing extracted receipt information with structured transaction fields.

How It Works​

The Process Receipt node extracts structured transaction data from receipt images. When executed, the node:

  1. Reads the receipt image file
  2. Applies country-specific receipt format recognition
  3. Performs orientation and skew correction if enabled
  4. Uploads the image to ABBYY Cloud
  5. Recognizes and extracts receipt fields (merchant, date, items, amounts, tax, total)
  6. Returns a task object with structured receipt data

Requirements​

  • Valid ABBYY Cloud credentials
  • Clear receipt image with readable text
  • Correct country selection for receipt format

Error Handling​

The node will return specific errors in the following cases:

  • Robomotion.ABBYYCloud.ErrImagePath - Image path is invalid or file not found
  • Robomotion.ABBYYCloud.ErrImageData - Cannot read image file
  • Robomotion.ABBYYCloud.ErrOption - Invalid country or image source option
  • Robomotion.ABBYYCloud.ErrDescription - Invalid description
  • Robomotion.ABBYYCloud.ErrPDFPassword - Invalid or incorrect PDF password

Usage Example​

Scenario: Extract expense data from a restaurant receipt

1. Process Receipt node:
   - Image Path: "C:/receipts/dinner_2024_01_15.jpg"
   - Country: USA
   - Image Source: Photo
   - Correct Orientation: true
   - Correct Skew: true
   - Write Extended Character Info: true

2. Wait Task node:
   - Task: {{ $.task }}
   - Timeout: 30 seconds

3. Extract receipt data:
   - Merchant Name
   - Date & Time
   - Line Items
   - Subtotal
   - Tax Amount
   - Total Amount
   - Payment Method

Common Use Cases​

  • Expense Management - Digitize receipts for expense reports
  • Accounting Automation - Import receipt data into accounting systems
  • Tax Compliance - Archive receipts for tax purposes
  • Budget Tracking - Monitor spending by category
  • Reimbursement Processing - Automate employee reimbursements
  • Mobile Expense Apps - Integrate receipt scanning in mobile applications
  • Receipt Validation - Verify purchase details and amounts
  • Financial Analytics - Analyze spending patterns from receipts

Extracted Information​

The node typically extracts the following fields:

  • Merchant Information:
    • Business name
    • Address
    • Phone number
    • Tax ID/VAT number
  • Transaction Details:
    • Date and time
    • Receipt/transaction number
    • Cashier/server information
  • Line Items:
    • Item descriptions
    • Quantities
    • Unit prices
    • Line totals
  • Financial Totals:
    • Subtotal
    • Tax amount
    • Tip/gratuity
    • Discount
    • Total amount
  • Payment Information:
    • Payment method
    • Card type (last 4 digits)
    • Change given

Tips and Best Practices​

  • Image Capture:
    • Flatten receipt before capturing
    • Use good lighting without shadows
    • Ensure entire receipt is visible
    • Avoid crumpled or damaged receipts
    • Capture immediately (receipts fade over time)
    • Use at least 300 DPI for scanning
  • Country Selection:
    • Select the correct country for receipt format
    • Different countries have different receipt layouts
    • Country setting affects field detection accuracy
    • Use "USA" for North American receipts
    • Select local country for best results
  • Image Source:
    • Set to "Photo" for smartphone captures
    • Set to "Scanner" for flatbed scans
    • Photo mode optimizes for camera images
  • Orientation and Skew:
    • Enable corrections for handheld photos
    • Critical for rotated or angled captures
    • Improves field detection reliability
  • Receipt Types:
    • Works with retail receipts
    • Restaurant and food service receipts
    • Gas station receipts
    • Hotel invoices
    • Service receipts
  • Data Validation:
    • Verify total matches sum of items
    • Check date format and validity
    • Validate tax calculations
    • Cross-check important amounts
    • Implement manual review for large amounts
  • Batch Processing:
    • Process multiple receipts in sequence
    • Use consistent file naming (date-based)
    • Enable Continue On Error for batch reliability
    • Group receipts by category or time period
  • Storage and Compliance:
    • Keep original images for audit purposes
    • Export to structured format (XML, JSON)
    • Link images to extracted data
    • Follow retention policies for tax compliance
  • Quality Issues:
    • Thermal receipts fade quickly - scan soon
    • Handle poor print quality with higher DPI
    • Retry with better lighting if recognition fails
    • Manual entry may be needed for damaged receipts
  • Integration:
    • Export to accounting software formats
    • Map fields to expense categories
    • Auto-categorize by merchant name
    • Flag duplicates and unusual amounts