OCR Processing Use Cases (OCR)¶

Module Purpose: Extract text from scanned documents and images. This module contains 6 use cases.

Use Case Quick Reference¶

ID	Title	Priority
OCR-001	Queue OCR Job	P1
OCR-002	Detect Document Language	P1
OCR-003	Execute OCR Engine	P1
OCR-004	Extract Tables	P2
OCR-005	Extract Forms/Fields	P2
OCR-006	Handle Multi-Page PDFs	P1

UC-OCR-001: Queue OCR Job¶

Overview¶

Field	Value
ID	OCR-001
Title	Queue OCR Job
Actor	System
Priority	P1 (MVP Phase 2)

Description¶

Add document to OCR processing queue based on file type and characteristics.

Queue Routing¶

Condition	Queue	Priority
Image file	ocr_high	High
Scanned PDF	ocr_high	High
Hybrid PDF	ocr_medium	Medium
Native PDF	text_extract	Low

Steps¶

Analyze file to determine OCR need
Select appropriate queue based on file type
Create OCR job record
Enqueue with priority

Output¶

{
  "job_id": "ocr_job_123",
  "document_id": "doc_abc",
  "queue": "ocr_high",
  "estimated_time": 30
}

Acceptance Criteria¶

Correct queue selection based on file type
Job tracking and status updates
Retry mechanism for failures

UC-OCR-002: Detect Document Language¶

Overview¶

Field	Value
ID	OCR-002
Title	Detect Document Language
Actor	OCR Worker
Priority	P1 (MVP Phase 2)

Description¶

Detect the primary language of the document to optimize OCR settings.

Supported Languages¶

Language	Code	OCR Model
English	eng	tesseract/eng
Hindi	hin	tesseract/hin
Marathi	mar	tesseract/mar
Tamil	tam	tesseract/tam

Steps¶

Sample text from document (first page)
Run language detection algorithm
Select OCR language pack
Configure OCR engine with language

Output¶

{
  "detected_language": "eng",
  "confidence": 0.95,
  "alternatives": [
    {"language": "hin", "confidence": 0.03}
  ]
}

Acceptance Criteria¶

Primary language detected correctly
Multi-language documents handled
Fallback to English if detection fails

UC-OCR-003: Execute OCR Engine¶

Overview¶

Field	Value
ID	OCR-003
Title	Execute OCR Engine
Actor	OCR Worker
Priority	P1 (MVP Phase 2)

Description¶

Run OCR engine on document to extract text.

Engine Configuration¶

Setting	Value
Engine	Tesseract 5
OEM	3 (LSTM)
PSM	6 (Block of text)
DPI	300

Steps¶

Preprocess image (deskew, denoise, binarize)
Set OCR engine parameters
Run OCR on each page
Collect text output with confidence scores
Store extracted text

Output¶

{
  "document_id": "doc_abc",
  "pages": [
    {
      "page_number": 1,
      "text": "INVOICE\n\nInvoice #12345...",
      "confidence": 0.92
    }
  ],
  "total_confidence": 0.91,
  "processing_time_ms": 2500
}

Acceptance Criteria¶

Text extracted from all pages
Confidence score per page
Processing time <5s for typical documents

UC-OCR-004: Extract Tables¶

Overview¶

Field	Value
ID	OCR-004
Title	Extract Tables
Actor	OCR Worker
Priority	P2 (MVP Phase 3)

Description¶

Detect and extract tabular data from documents.

Steps¶

Detect table regions in document
Extract cell boundaries
OCR each cell
Structure as rows/columns
Return as JSON or CSV

Output¶

{
  "document_id": "doc_abc",
  "tables": [
    {
      "page": 1,
      "rows": [
        ["Item", "Quantity", "Price"],
        ["Widget", "10", "$50.00"],
        ["Gadget", "5", "$75.00"]
      ]
    }
  ]
}

Acceptance Criteria¶

Tables detected automatically
Cell content extracted correctly
Export as CSV available

UC-OCR-005: Extract Forms/Fields¶

Overview¶

Field	Value
ID	OCR-005
Title	Extract Forms/Fields
Actor	OCR Worker
Priority	P2 (MVP Phase 3)

Description¶

Extract key-value pairs from form documents.

Steps¶

Detect form layout
Identify label-value pairs
Extract field values
Return structured data

Output¶

{
  "document_id": "doc_abc",
  "fields": {
    "Name": "John Smith",
    "Date": "2024-01-15",
    "Amount": "$5,000.00"
  }
}

Acceptance Criteria¶

Key-value pairs extracted
Common form fields recognized

UC-OCR-006: Handle Multi-Page PDFs¶

Overview¶

Field	Value
ID	OCR-006
Title	Handle Multi-Page PDFs
Actor	OCR Worker
Priority	P1 (MVP Phase 2)

Description¶

Process multi-page PDF documents efficiently.

Steps¶

Extract page count from PDF
Convert each page to image
OCR pages in parallel (configurable concurrency)
Combine text from all pages
Track per-page confidence

Configuration¶

Setting	Value
Max pages	100
Parallel workers	4
Page timeout	60s

Acceptance Criteria¶

All pages processed
Page order preserved
Large documents handled without timeout

← Back to Use Cases | Previous: Tagging | Next: Search →