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Performance Evaluation A framework for Performance Analysis of OCR methods

Layout Evaluation

Overview

This tool is part of a framework for evaluating the performance of layout analysis methods. It combines efficiency and accuracy by using a special interval based geometric representation of regions. A wide range of sophisticated evaluation measures provides the means for a deep insight into the analysed systems, which goes far beyond simple benchmarking. The support of user-defined profiles allows the tuning for practically any kind of evaluation scenario related to real world applications.

The framework has been successfully delivered as part of a major EU-funded project (IMPACT) to evaluate large-scale digitisation projects and has been validated applied within the past three ICDAR Page Segmentation Competitions.

Features

  • Evaluation Profile editor with Novel Metrics
    • Fully customisable metrics for different Region Types (Text, Image, Table, ...)
    • Fully customisable metrics for different Error Types (Merge, Split, Miss, Partial Miss, False Detection and Missclassification)
    • All possible combinations of Region Types and Error Types can be defined
    • Support for Reading Order (using boh ordered and unordered groups)
  • Evaluation result viewer, featuring:
    • Colour and pattern coded, interactive overlay on the document image
    • Highlights segmentation and classification errors

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Text Evaluation

Overview

The Text Evaluation tool implements the word and character accuracy measures developed by the University of Nevada Las Vegas (UNLV dissertation by S. V. Rice). It has been complemented by a bag-of-words method which is independent from the reading order.

Interfaces

The tool is platform independent and comes with a basic graphical user interface as well as a command line interface.

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Related Publications

A survey of OCR evaluation tools and metrics

C. Neudecker, K. Baierer, C. Clausner, A. Antonacopoulos, S. Pletschacher

In The 6th International Workshop on Historical Document Imaging and Processing (HIP '21). Association for Computing Machinery, New York, NY, USA, 13–18.

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Flexible character accuracy measure for reading-order-independent evaluation

C. Clausner, S. Pletschacher, A. Antonacopoulos

Pattern Recognition Letters, Volume 131, March 2020, Pages 390-397

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Quality Prediction System for Large-Scale Digitisation Workflows

C. Clausner, S. Pletschacher, A. Antonacopoulos

Proceedings of the 12th IAPR International Workshop on Document Analysis Systems (DAS2016), Santorini, Greece, April 11-14, 2016

Details »  Download PDF