Enhancement and cleaning of handwritten data by using neural networks

被引：0
作者：
Hidalgo, JL [1 ]
España, S
Castro, MJ
Pérez, JA
机构：
[1] Univ Politecn Valencia, Dept Sistemas Informat & Computac, E-46071 Valencia, Spain
[2] Univ Politecn Valencia, Dept Informat Sistemas & Computadores, E-46071 Valencia, Spain
来源：
PATTERN RECOGNITION AND IMAGE ANALYSIS, PT 1, PROCEEDINGS | 2005年 / 3522卷
关键词：
handwritten recognition; form processing; image enhancement; image denoising; artificial neural networks;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work, artificial neural networks are used to clean and enhance scanned images for a handwritten recognition task. Multilayer perceptrons are trained in a supervised way using a set of simulated noisy images together with the corresponding clean images for the desired output. The neural network acquires the function of a desired enhancing method. The performance of this method has been evaluated for both noisy artificial and natural images. Objective and subjective methods of evaluation have shown a superior performance of the proposed method over other conventional enhancing and cleaning filters.
引用
收藏
页码：376 / 383
页数：8
相关论文
共 50 条
  • [41] Efficient Luminosity Enhancement in Human Brain Images using Pulse-Coupled Neural Networks
    Aguilar Dominguez, Kevin S.
    Mejia Lavalle, Manuel
    Sossa, Humberto
    COMPUTACION Y SISTEMAS, 2020, 24 (01): : 105 - 120
  • [42] New approaches to processing GIS Data using Artificial Neural Networks models
    Mihai, Dana
    ANNALS OF THE UNIVERSITY OF CRAIOVA-MATHEMATICS AND COMPUTER SCIENCE SERIES, 2021, 48 (02): : 358 - 373
  • [43] 3D inversion of DC data using artificial neural networks
    Ahmad Neyamadpour
    W. A. T. Wan Abdullah
    Samsudin Taib
    Danesh Niamadpour
    Studia Geophysica et Geodaetica, 2010, 54 : 465 - 485
  • [44] Precipitation data fusion using vector space transformation and artificial neural networks
    Turlapaty, Anish C.
    Anantharaj, Valentine G.
    Younan, Nicolas H.
    Turk, F. Joseph
    PATTERN RECOGNITION LETTERS, 2010, 31 (10) : 1184 - 1200
  • [45] Method for Automatic Detection of Traffic Incidents Using Neural Networks and Traffic Data
    Ki, Yong-Kul
    Kim, Joong-Hyo
    Kim, Tae-Kyoung
    Heo, Nak-Won
    Choi, Jin-Wook
    Jeong, Jun-Ha
    2018 IEEE 9TH ANNUAL INFORMATION TECHNOLOGY, ELECTRONICS AND MOBILE COMMUNICATION CONFERENCE (IEMCON), 2018, : 184 - 188
  • [46] Processing Landsat TM data using complex-valued neural networks
    Michel, HE
    Kunjithapatham, S
    DATA MINING AND KNOWLEDGE DISCOVERY: THEORY, TOOLS AND TECHNOLOGY IV, 2002, 4730 : 43 - 51
  • [47] Analysis of Prediction of Pressure Data in Oil Wells Using Artificial Neural Networks
    Romero-Salcedo, M.
    Ramirez-Sabag, J.
    Lopez, H.
    Hernandez, D. A.
    Ramirez, R.
    2010 IEEE ELECTRONICS, ROBOTICS AND AUTOMOTIVE MECHANICS CONFERENCE (CERMA 2010), 2010, : 51 - 55
  • [48] Data-Driven Modeling of Biodiesel Production Using Artificial Neural Networks
    Mogilicharla, Anitha
    Reddy, P. Swapna
    CHEMICAL ENGINEERING & TECHNOLOGY, 2021, 44 (05) : 901 - 905
  • [49] 3D INVERSION OF DC DATA USING ARTIFICIAL NEURAL NETWORKS
    Neyamadpour, Ahmad
    Abdullah, W. A. T. Wan
    Taib, Samsudin
    Niamadpour, Danesh
    STUDIA GEOPHYSICA ET GEODAETICA, 2010, 54 (03) : 465 - 485
  • [50] A Data Cleansing Approach In Smart Home Environments Using Artificial Neural Networks
    Titouna, Chafiq
    Nait-Abdesselam, Farid
    Darwaish, Asim
    2020 16TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS (WIMOB), 2020,
12345