rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Logo recognition
    sub title: theory and practice
  name:
    name part: Chen, Jingying
    name part: 1973-
    role:
      role term: creator
  name:
    name part: Wang, Lizhe
    name part: 1974-
  name:
    name part: Chen, Dan
    name part: 1973-
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    place:
      place term: Boca Raton, FL
    publisher: CRC Press
    date issued: ©2012
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xvi, 176 pages) : illustrations
  abstract: "Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Recognition: Theory and Practice is the first book to focus on logo recognition, especially under noisy conditions. Beginning with an introduction to fundamental concepts and methods in pattern and shape recognition, it surveys advances in logo recognition. The authors also propose a new logo recognition system that can be used under adverse conditions such as broken lines, added noise, and occlusion. The proposed system introduces a novel polygonal approximation, a robust indexing scheme, and a new Line Segment Hausdorff Distance (LHD) matching method that can handle more distortion and transformation types than previous techniques. In the first stage, raw logos are transformed into normalized line segment maps. In the second stage, effective line pattern features are used to index the database in order to generate a moderate number of likely models. In the third stage, an improved LHD measure screens and generates the best matches. A comprehensive overview of logo recognition, the book also presents successful applications of the technology and suggests directions for future research."--Provided by publisher
  abstract: "Preface Logo recognition is of great interest in the document and shape matching domain. Logos can act as a valuable means of identifying sources of documents. By recognizing the logo, semantic information about the document is obtained which may be useful to decide whether or not to analyze the textual parts. Some promising results have been found for clean logos; however, they can hardly be robust for noisy logos. This book summarizes our recent research on logo recognition. We first in this book (Chapter 2) provide some introduction and fundamental knowledge for pattern recognition. Readers can safely skip reading it if you feel you are familiar with these topics. In order to develop a logo recognition method that is robust to be employed under adverse conditions such as different broken curves, added noise and occlusion, a logo recognition system based on line pattern features is proposed in this book. To achieve the desired accuracy and effciency, the proposed system employs a three-stage hierarchy, polygonal approximation, indexing and matching. In the first stage, the raw logos are transformed into normalized line segment maps (LSM); in the second stage, effective line pattern features are used to index the database to generate a moderate number of likely models with respect to a test image; in the third stage, an improved Line Segment Hausdor Distance (LHD) measure is proposed to screen further and generate the best matches"--Provided by publisher
  table of contents: 1. Introduction -- 2. Preliminary knowledge -- 3. Review of shape recognition techniques -- 4. System overview -- 5. Polygonal approximation -- 6. Logo indexing -- 7. Logo matching -- 8. Applications -- 9. Conclusion.
  note: Jingying Chen, Lizhe Wang, Dan Chen.
  note: Title from PDF title page (viewed November 1, 2011).
  note: Includes bibliographical references and index.
  subject:
    topic: Pattern recognition systems
  subject:
    topic: Logos (Symbols)
  subject:
    topic: Document imaging systems
  subject:
    topic: Pattern Recognition, Automated
  subject:
    topic: Reconnaissance des formes (Informatique)
  subject:
    topic: Logos (Symboles)
  subject:
    topic: Gestion électronique de documents
  subject:
    topic: logos
  subject:
    topic: COMPUTERS
    topic: Enterprise Applications
    topic: Business Intelligence Tools
  subject:
    topic: COMPUTERS
    topic: Intelligence (AI) & Semantics
  subject:
    topic: Document imaging systems
  subject:
    topic: Logos (Symbols)
  subject:
    topic: Pattern recognition systems
  classification: TK7882.P3 C475 2012e
  classification: 006.3
  classification: COM021030 COM037000 TEC015000
  related item:
    title info:
      title: Logo recognition
    name:
      name part: Chen, Jingying, 1973 -
    origin info:
      publisher: Boca Raton, FL : CRC Press, ©2012
    identifier: (DLC) 2011030495
    identifier: (OCoLC)606777044
  identifier: 9781439847855
  identifier: 1439847851
  identifier: 9781315217475
  identifier: 1315217473
  identifier: 9781351824675
  identifier: 1351824678
  identifier: 9781439847756
  identifier: 1439847754
  identifier: 9781138116757
  identifier: 2011030495
  identifier: CL0500000530 Safari Books Online
  identifier: http://proxy.library.tamu.edu/login
  identifier: https://go.oreilly.com/TAMU/library/view/-/9781439847756/
  record info:
    record content source: UV0
    record creation date: 111031
    record change date: 20241108170204.6
    record identifier: in00005525091
    language of cataloging:
      language term: eng