feat: add VIN photo OCR pipeline (refs #67)

Implement VIN-specific OCR extraction with optimized preprocessing:

- Add POST /extract/vin endpoint for VIN extraction
- VIN preprocessor: CLAHE, deskew, denoise, adaptive threshold
- VIN validator: check digit validation, OCR error correction (I->1, O->0)
- VIN extractor: PSM modes 6/7/8, character whitelist, alternatives
- Response includes confidence, bounding box, and alternatives
- Unit tests for validator and preprocessor
- Integration tests for VIN extraction endpoint

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

ocr/app/extractors/base.py

@@ -0,0 +1,47 @@
+"""Base extractor class for domain-specific OCR extraction."""
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import Any, Optional
+
+
+@dataclass
+class ExtractionResult:
+    """Base result for extraction operations."""
+
+    success: bool
+    confidence: float
+    raw_text: str
+    processing_time_ms: int
+    extracted_data: dict[str, Any] = field(default_factory=dict)
+    error: Optional[str] = None
+
+
+class BaseExtractor(ABC):
+    """Abstract base class for domain-specific extractors."""
+
+    @abstractmethod
+    def extract(self, image_bytes: bytes, content_type: Optional[str] = None) -> ExtractionResult:
+        """
+        Extract domain-specific data from an image.
+
+        Args:
+            image_bytes: Raw image bytes
+            content_type: MIME type of the image
+
+        Returns:
+            ExtractionResult with extracted data
+        """
+        pass
+
+    @abstractmethod
+    def validate(self, data: Any) -> bool:
+        """
+        Validate extracted data.
+
+        Args:
+            data: Extracted data to validate
+
+        Returns:
+            True if data is valid
+        """
+        pass