A recognition algorithm of printed or handwritten digits of the ZIP code

被引:0
|
作者
Flores, EL [1 ]
机构
[1] Univ Fed Uberlandia, Dept Engn Eletr, BR-38400902 Uberlandia, MG, Brazil
关键词
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
This paper describes an algorithm that carries out the recognition of printed or handwritten digits through the verification of intrinsic and common characteristics Verifying such characteristics the algorithm tries to come close to the recognition process used by the human being. This algorithm carries out the segmentation of the overlapped digits, scanning the entire digit and copying the pixels-on and the pixels-off-scanned, to a matrix This matrix can contain isolated or connected digits. The segmentation of connected digits is carried out by the analysis of the quantity of upper and lower horizontal lines that are found in the matrix and of the crossing points found in the interval comprehended between 80% to 140% of the mean width of digits contained in this matrix Various tests were carried out to recognize the printed or handwritten digits of the ZIP code in correspondence and the percentage of accuracy obtained war of 99.99%. The principal characteristics that this algorithm possesses are: the recognition of the handwritten characters regardless of who wrote them; the recognition of characters regardless of their size and of the position in which the character was written; satisfactory performance even in the presence of noise and high accuracy rate.
引用
收藏
页码:671 / 676
页数:6
相关论文
共 50 条
  • [31] Representation and recognition of handwritten digits using deformable templates
    Jain, AK
    Zongker, D
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 1997, 19 (12) : 1386 - 1391
  • [32] Handwritten Digits Recognition Using Multiple Instance Learning
    Yuan Hanning
    Wang Peng
    2013 IEEE INTERNATIONAL CONFERENCE ON GRANULAR COMPUTING (GRC), 2013, : 408 - 411
  • [33] Classification and recognition of handwritten digits by using mathematical morphology
    Vijaya kumar V.
    Srikrishna A.
    Babu B.R.
    Mani M.R.
    Sadhana, 2010, 35 (4) : 419 - 426
  • [34] Reliable Recognition of Handwritten Digits Using Hamming Network
    Archana, S.
    Madhavi, B. K.
    Krishna, I. V. Murali
    2016 IEEE 6TH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTING (IACC), 2016, : 476 - 479
  • [35] Handwritten Digits Recognition Based on Swarm Optimization Methods
    Nebti, Salima
    Boukerram, Abdellah
    NETWORKED DIGITAL TECHNOLOGIES, PT 1, 2010, 87 : 45 - 54
  • [36] ALGEBRAIC FUSION OF MULTIPLE CLASSIFIERS FOR HANDWRITTEN DIGITS RECOGNITION
    Zhao, Huihuang
    Liu, Han
    PROCEEDINGS OF 2018 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION (ICWAPR), 2018, : 250 - 255
  • [37] One novel phog descriptor for handwritten digits recognition
    Zhang, Hongyan
    Lei, Genping
    ICIC Express Letters, Part B: Applications, 2016, 7 (03): : 607 - 612
  • [38] A study on handwritten digits recognition using independent components
    Kotani, M
    Ozawa, S
    8TH INTERNATIONAL CONFERENCE ON NEURAL INFORMATION PROCESSING, VOLS 1-3, PROCEEDING, 2001, : 1620 - 1625
  • [39] Classification and recognition of handwritten digits by using mathematical morphology
    Kumar, V. Vijaya
    Srikrishna, A.
    Babu, B. Raveendra
    Mani, M. Radhika
    SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES, 2010, 35 (04): : 419 - 426
  • [40] Hybrid neural models for automatic handwritten digits recognition
    Peres, Aline A.
    Vieira, Susana M.
    Caldas Pinto, Joao R.
    2018 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2018, : 543 - 550