Image-based VIN capture

VINocr API

VINocr extracts VINs from images of labels, receipts, invoices, documents, vehicle tags, and other visual sources where manual entry would be slow or error-prone.

The service is designed for server-side integration and returns structured recognition output that can be reviewed, stored, or passed into VINdecode and other workflows.

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Capture Printed VINs

Reduce manual typing when VINs are present in images or scanned documents.

Image Input

Accept still images that contain a printed VIN, such as photos of labels, receipts, invoices, and documents.

Recognition Output

Return the recognized VIN and location metadata that your application can display for review.

Workflow Support

Pass the extracted VIN into VINdecode, VINfix, claim intake, inspection, service, or inventory workflows.

Typical Integration Flow

Keep image upload and token handling behind your server-side application.

Step 1

Upload Image

Capture or upload an image that contains a visible VIN.

Step 2

Call VINocr

Your backend sends the image with a valid bearer token.

Step 3

Review VIN

Display the extracted VIN and bounding location for verification.

Step 4

Continue

Use the captured VIN in downstream vehicle-data workflows.

Image Guidance

Recognition quality depends on source image quality.

Best Results

Use clear, focused still images.
Keep the VIN area readable and well lit.
Avoid heavy glare, blur, and complex backgrounds.

Human Review

OCR output should be reviewed when the image is noisy, the font is very small, or the VIN is partially obscured. Review is still faster than retyping the VIN character by character.

Recognition Examples

Sample image, recognized VIN region, and structured result.

Sample Image

JSON Data

{
  "vin_captured": "19UYA42601A019296",
  "left": 54,
  "top": 289,
  "width": 445,
  "height": 22
}

XML Data

<VINocr>
  <VIN_Captured>19UYA42601A019296</VIN>
  <Left>54</Left>
  <Top>289</Top>
  <Width>445</Width>
  <Height>22</Height>
</VINocr>

Sample Image

JSON Data

{
  "vin_captured": "JF1BL5LJ35G002001",
  "left": 113,
  "top": 54,
  "width": 158,
  "height": 11
}

XML Data

<VINocr>
  <VIN_Captured>JF1BL5LJ35G002001</VIN>
  <Left>113</Left>
  <Top>54</Top>
  <Width>158</Width>
  <Height>11</Height>
</VINocr>

Sample Image

JSON Data

{
  "vin_captured": "WP0AC2A999S783477",
  "left": 45,
  "top": 61,
  "width": 190,
  "height": 46
}

XML Data

<VINocr>
  <VIN_Captured>WP0AC2A999S783477</VIN>
  <Left>45</Left>
  <Top>61</Top>
  <Width>190</Width>
  <Height>46</Height>
</VINocr>

Try VINocr

Submit a sample image and inspect JSON or XML recognition output.

Open VINocr Demo