Powered by OPF
OPF WIKI STATIC ARCHIVE
2,681 pages · 153 spaces · 776 tags · 4,025 history records · 96.2% of the original wiki recovered
Archived copy. This page was recovered from the Internet Archive snapshot of /display/TR/Matchbox Tool taken on 2013-02-12. The original wiki at wiki.opf-labs.org is being decommissioned.

Matchbox Tool

Created by Roman Graf on Feb 07, 2013 · last edited by Roman Graf · on Feb 07, 2013 (view history)

Summary

Purpose Matchbox: Duplicate detection tool for digital document collections.
Homepage
https://github.com/openplanets/scape/tree/master/pc-qa-matchbox
Source Code Repository
https://github.com/openplanets/scape/tree/master/pc-qa-matchbox
License
Open source
Debian Package http://packages.debian.org/stable/package

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:

Image processing method:

The image processing algorithm can be described in 4 steps:
1. Document feature extraction

2. Learning visual dictionary

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)

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] [\--sdk SDK] [\--precluster PRECLUSTER] [\--clahe CLAHE] [\--config CONFIG] [\--featdir FEATDIR] [\--bowsize BOWSIZE] [\--csv] [-v] dir all,extract,compare,train,bowhist,clean

User Experiences

currently installed at Austrian National Library

News Feeds

PRONOM updates

Release Feed

Activity Feed