Matchbox Tool

Matchbox: Duplicate detection tool for digital document collections.
Homepage:	https://github.com/openplanets/scape/tree/master/pc-qa-matchbox
License:	Open source

Description

The Matchbox tool is responsible for finding duplicatre pairs in a collection of digital documents based on SIFT features and SSIM methods. Consequently the tool takes a collection path with associated parameters as input. Currently three scenarios are implemented. These are:

• Duplicate search in one turn (parameter ‘all’)

• Professional duplicate search (experienced user can execute particular step in ‘FindDuplicates’ workflow)

• Quick check if two documents are duplicates (based on previous BoW dictionary).

Further parameters that influence and adjust duplicate analysis are currently investigated.

Image processing method:

The image processing algorithm can be described in 4 steps:

1. Document feature extraction

• Interest point detection (applying Scale Invariant Feature Transform (SIFT) keypoint extraction)
• Derivation of local feature descriptors (invariant to geometrical or radiometrical distortions)

2. Learning visual dictionary

• Clustering method applied to all SIFT descriptors of all images using k-means algorithm
• Run over collection and collect local descriptors in a visual dictionary using Bag-Of-Words (BoW) algorithm

3. Create visual histogram for each image document

4. Detect similar images based on visual histogram and local descriptors. Evaluate similarity score — pair-wise comparison of corresponding keyword frequency histograms for all documents. Conduct structural similarity analysis applying Sturctural SIMilarity (SSIM) approach (1 means identical and 0 means very different)

• Rotate
• Scale
• Mask
• Overlaying

Usage:

FindDuplicates script can be invoked from command line. For standard usage two parameters are required: path to the collection documents and ‘all’.

scape/pc-qa-matchbox/Python# python2.7 FindDuplicates.py h

usage: FindDuplicates.py [-h] [-threads THREADS|—threads THREADS] [-sdk SDK|—sdk SDK] [-precluster PRECLUSTER|—precluster PRECLUSTER] [-clahe CLAHE|—clahe CLAHE] [-config CONFIG|—config CONFIG] [-featdir FEATDIR|—featdir FEATDIR] [-bowsize BOWSIZE|—bowsize BOWSIZE] [-csv|—csv] [-v] dir all,extract,compare,train,bowhist,clean

User Experiences

currently installed at Austrian National Library