Signature Detection

A simple tool to detect if there are signatures in an image or a PDF file.

The full documentation is presented at the Github Repository.

Extra Dependencies

This tool uses Wand to convert a PDF file into images.

Wand is a ctypes-based simple ImageMagick binding for Python. You may need to install ImageMagick on your local machine.

More details are available here.

Usage

Signature_detect contains 4 classes.

1. Loader
2. Extractor
3. Cropper
4. Judger

Loader

Loader can read an image or a PDF file page by page.

It returns a list of the masks. Each mask is a numpy 2 dimensions array. Its element's value is 0 or 255.

from signature_detect.loader import Loader

loader = Loader(
    low_threshold=(0, 0, 250), 
    high_threshold=(255, 255, 255))

masks = loader.get_masks(file_path)

Extractor

Extractor reads a mask, labels the regions in the mask, and removes both small and big regions. We consider that the signature is a region of middle size.

from signature_detect.extractor import Extractor

extractor = Extractor(
    outlier_weight=3, 
    outlier_bias=100, 
    amplfier=10, 
    min_area_size=10)

labeled_mask = extractor.extract(mask)

Cropper

Cropper crops the regions in the labeled mask.

from signature_detect.cropper import Cropper

cropper = Cropper(
    min_region_size=10000, 
    border_ratio=0.1)

results = cropper.run(labeled_mask)

Judger

Judger decides whether a region is a signature.

from signature_detect.judger import Judger

judger = Judger(
    size_ratio=[1, 4], 
    pixel_ratio=[0.01, 1])

is_signed = judger.judge(result["cropped_mask"])

Dev version

If you would like to develop this package and run the tests, you can download the code and install dev environment locally.

pip install -e .[dev]