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Limina supports scanning images for PII and creating de-identified or redacted copies. Limina’s supported entity types function across each file type, with localized variants of different PII (Personally Identifiable Information) entities, PHI (Protected Health Information) entities, and PCI (Payment Card Industry) entities being detected. Our Supported Languages and Supported Entity Types page provides a more detailed look.
If you’d like to try it yourself, please visit our free interactive web demo. No code or account is necessary.

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How Images Are Processed

Image files are processed as follows:
  1. Non-text PII such as faces and license plates are detected.
  2. Additionally the image is run through an OCR system to detect any text present.
  3. The output of the OCR system is then passed to a PII detection module.
  4. Any PII found in the previous steps is de-identified via blurring or black box redaction.
You can configure the OCR System by setting it as an Environment Variable or sending it in the request object. Check out our OCR Guide to further understand the OCR modes and their usage.

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Constraints

  • There is limited support for 8-bit PNG images.
  • Multi-page TIFF images are only supported on versions >=4.2.1. Earlier versions will process and return the first page of a multi-page TIFF.

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Supported File Types

File TypeExtensionContent TypeAdded In
JPEG image.jpg, .jpegimage/jpg, image/jpeg3.0.0
TIFF image.tif, .tiffimage/tif, image/tiff3.0.0
PNG image.pngimage/png3.4.0
BMP image.bmpimage/bmp, image/x-ms-bmp3.4.0
GIF image.gifimage/gif4.2.1

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Support Matrix

CPU ContainerGPU ContainerCommunity APIProfessional API
SupportedYesYesUp to 10 MiBNo

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Sample Request

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{
  "file": {
    "data": "<file_content_base64>",
    "content_type": "image/jpeg"
  },
  "entity_detection": {
    "return_entity": true
  }
}

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Sample Response

Response
{
  "processed_file": "Base64 Encoded File Content of the Redacted File",
  "processed_text": "string",
  "entities": "List[Entity]",
  "entities_present": true,
  "languages_detected": {"lang_1": 0.67, "lang_2": 0.74}
}