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H J Zhang - One of the best experts on this subject based on the ideXlab platform.

  • An Automatic Performance Evaluation Protocol for Video Text Detection Algorithms
    IEEE Transactions on Circuits and Systems for Video Technology, 2004
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    Text presented in videos provides important supplemental information for video indexing and retrieval. Many efforts have been made for text detection in videos. However, there is still a lack of performance evaluation protocols for video text detection. In this paper, we propose an objective and comprehensive performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at the Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore tolerant to different ground-truth difficulties to a certain degree. We also assign a detectability index (DI) value to each ground-truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground-truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied to performance evaluation of a text detection approach to determine the best thresholds that can yield the best detection results. The protocol has also been employed to compare the performances of several text detection systems. Hence, we believe that the proposed protocol can be used to compare the performance of different video/image text detection algorithms/systems and can even help improve, select, and design new text detection methods.

  • ICDAR - Automatic performance evaluation for video text detection
    Proceedings of Sixth International Conference on Document Analysis and Recognition, 1
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    We propose an objective, comprehensive and difficulty-independent performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore independent of the ground truth difficulty. We also assign a detection importance (DI) level to each ground truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied on a text detection approach to determine the best parameters that can yield the best detection results.

Liu Wenyin - One of the best experts on this subject based on the ideXlab platform.

  • An Automatic Performance Evaluation Protocol for Video Text Detection Algorithms
    IEEE Transactions on Circuits and Systems for Video Technology, 2004
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    Text presented in videos provides important supplemental information for video indexing and retrieval. Many efforts have been made for text detection in videos. However, there is still a lack of performance evaluation protocols for video text detection. In this paper, we propose an objective and comprehensive performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at the Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore tolerant to different ground-truth difficulties to a certain degree. We also assign a detectability index (DI) value to each ground-truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground-truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied to performance evaluation of a text detection approach to determine the best thresholds that can yield the best detection results. The protocol has also been employed to compare the performances of several text detection systems. Hence, we believe that the proposed protocol can be used to compare the performance of different video/image text detection algorithms/systems and can even help improve, select, and design new text detection methods.

  • GREC - Object-Process Based Segmentation and Recognition of ANSI and ISO Standard Dimensioning Texts
    Graphics Recognition Methods and Applications, 1996
    Co-Authors: Dov Dori, Yelena Velkovitch, Liu Wenyin
    Abstract:

    Recognition of dimensioning text in engineering drawings is an essential part of the dimension understanding process, since this text is an important component of the dimension-set. We first introduce the OPD expression of the structural relations among the dimension-set components and the illustration of ISO and ANSI drafting standards. We then present principles and implementation of a method of segmentation and recognition of dimension text in ANSI and ISO based drawings. The method is vector-based, implying that the input is a set of vectors-wires (bars and arcs)-resulting from the orthogonal zig-zag vectorization, arc segmentation, and arrowhead pair recognition. Initial Textbox extraction is done by a region growing process, performed on text-wire candidates. On the basis of Textbox context (neighboring annotation wires), the drafting standard is detected. Raw Textboxes are divided into logical Textboxes, which are further decomposed into basic Textboxes. A neural network based OCR algorithm is applied to each single character image decomposed from the basic Textboxes and the symbol in each basic Textbox in recognized. Finally, the OCR recognition results are verified by using contextual information and comparing the results with the measurements made directly on the drawing.

  • SSPR - Vector-Based Segmentation of Text Connected to Graphics in Engineering Drawings
    Advances in Structural and Syntactical Pattern Recognition, 1996
    Co-Authors: Dov Dori, Liu Wenyin
    Abstract:

    A method for segmentation of text that may be connected to graphics in engineering drawings is presented. It consists of three steps: growing individual characterbox regions, using a recursive merging scheme by stroke linking; merging the detected characterboxes into a Textbox and determining its orientation; and re-segmenting the Textbox back into the refined characterbox that can be input to an OCR subsystem. The method can segment dimensioning text as well as other classes of text. It handles both isolated and touching characters, aligned at any slant. The capability of segmenting characters that touch either themselves or graphics, which is an important feature in handling real life drawings, is obtained by focusing on intermediate vector information rather that on the raw pixel data. We present the details of the algorithm and show both successful and unsuccessful examples from an experimental set of 36 dimensioning Textboxes, in which 94% segmentation rate was achieved with 3% false alarm rate.

  • ICDAR - Automatic performance evaluation for video text detection
    Proceedings of Sixth International Conference on Document Analysis and Recognition, 1
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    We propose an objective, comprehensive and difficulty-independent performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore independent of the ground truth difficulty. We also assign a detection importance (DI) level to each ground truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied on a text detection approach to determine the best parameters that can yield the best detection results.

X.-s. Hua - One of the best experts on this subject based on the ideXlab platform.

  • An Automatic Performance Evaluation Protocol for Video Text Detection Algorithms
    IEEE Transactions on Circuits and Systems for Video Technology, 2004
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    Text presented in videos provides important supplemental information for video indexing and retrieval. Many efforts have been made for text detection in videos. However, there is still a lack of performance evaluation protocols for video text detection. In this paper, we propose an objective and comprehensive performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at the Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore tolerant to different ground-truth difficulties to a certain degree. We also assign a detectability index (DI) value to each ground-truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground-truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied to performance evaluation of a text detection approach to determine the best thresholds that can yield the best detection results. The protocol has also been employed to compare the performances of several text detection systems. Hence, we believe that the proposed protocol can be used to compare the performance of different video/image text detection algorithms/systems and can even help improve, select, and design new text detection methods.

  • ICDAR - Automatic performance evaluation for video text detection
    Proceedings of Sixth International Conference on Document Analysis and Recognition, 1
    Co-Authors: X.-s. Hua, Liu Wenyin, H J Zhang
    Abstract:

    We propose an objective, comprehensive and difficulty-independent performance evaluation protocol for video text detection algorithms. The protocol includes a positive set and a negative set of indices at Textbox level, which evaluate the detection quality in terms of both location accuracy and fragmentation of the detected Textboxes. In the protocol, we assign a detection difficulty (DD) level to each ground truth Textbox. The performance indices can then be normalized with respect to the Textbox DD level and are therefore independent of the ground truth difficulty. We also assign a detection importance (DI) level to each ground truth Textbox. The overall detection rate is the DI-weighted average of the detection qualities of all ground truth Textboxes, which makes the detection rate more accurate to reveal the real performance. The automatic performance evaluation scheme has been applied on a text detection approach to determine the best parameters that can yield the best detection results.

Christof Schöch - One of the best experts on this subject based on the ideXlab platform.

  • The CLiGS Textbox: Building and Using Collections of Literary Texts in Romance Languages Encoded in TEI XML
    Journal of the Text Encoding Initiative, 2019
    Co-Authors: Christof Schöch, José Calvo Tello, Ulrike Henny-krahmer, Stefanie Popp
    Abstract:

    The CLiGS Textbox is published by the Computational Literary Genre Stylistics (CLiGS) group. The Textbox is the group’s publication channel for several collections of literary texts. We describe the rationale for the manner in which the collections of literary texts included in the Textbox have been compiled, annotated, and published. Furthermore, we suggest several ways in which the text collections can be used for research in literary studies. We aim to document some of the work of the CLiGS group, to showcase the unique TEI XML-based collections of French, Spanish, Spanish-American, and Portuguese novels and French drama we make available, and to encourage reuse of these text collections by others. We argue that agreement on common formats and procedures for text preparation, encoding, and publication fosters the accessibility, analysis, and reuse potential of literary text collections.

  • cligs/Textbox: Spring is coming release.
    2017
    Co-Authors: Christof Schöch, Ulrike Henny, José Calvo Tello
    Abstract:

    This release notably includes the following changes: The "romancesportuguesas" collection has been added The "theatre17" collection has been added Some unsuitable texts have been removed (this makes this release not backwards compatible with previous releases) Some of the ZIP versions have been removed (it is hard to keep them up to date) For details, see the version history here: https://github.com/cligs/Textbox/commits/nex

  • Cligs/Textbox: Advent Release
    2017
    Co-Authors: Christof Schöch, Ulrike Henny, José Calvo, Katrin Betz
    Abstract:

    This new release contains: A new collection of Italian Short Stories and Novellas (1880s-1920s) A new collection of Italian Novels (1850 and 1890) A new collection of Spanish Short Stories from 1880-1940 15 new novels in the Corpus of Spanish Novels from 1880-1940

  • cligs Textbox advent release
    2017
    Co-Authors: Christof Schöch, Ulrike Henny, José Calvo, Katrin Betz
    Abstract:

    This new release contains: A new collection of Italian Short Stories and Novellas (1880s-1920s) A new collection of Italian Novels (1850 and 1890) A new collection of Spanish Short Stories from 1880-1940 15 new novels in the Corpus of Spanish Novels from 1880-1940

  • How good are our texts, really? Quality assurance for literary texts from various sources
    2016
    Co-Authors: Christof Schöch
    Abstract:

    by Ulrike Henny and Christof Schoch -- this post originally appeared on the CLiGS blog. Some weeks ago, we made our "New Year's release" of text collections available. We publish the texts in the "CLiGS" group's GitHub repository called "Textbox" and archive each release on Zenodo where they get a DOI. The texts are encoded in TEI with relatively detailed metadata. The collections are subsets of the texts we are using in our various research projects in computational genre stylistics and con...

Stephen Dippel - One of the best experts on this subject based on the ideXlab platform.