Normal view MARC view ISBD view

Jawi recognition system / Nur Aziela Mansor

By:

Nur Aziela Mansor

Material type: Text

TextPublication details: Kuantan, Pahang : UMP, 2010Description: xiv, 61 p. : ill. (some col.) ; 30 cm. + 1 computer discISBN:

THE0007055(Local)

Other title:

Jawi recognition system [computer file]

Subject(s):

Dissertation note: Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010 Abstract: Character recognition plays an important role in the modern world. It can solve more complex problem and makes humans’ job easier. Jawi is one of the important character that we used in our daily life. Jawi script is an important Malay heritage that has been in general, replaced by the Roman script drastically. From a dominant writing in Malay world, the usage of Jawi is confined mostly in Islamic religious context nowadays. As an initiative to encourage the learning of Jawi, this research proposed Jawi Character Recognition system using Neural Network and Supervised Learning method. The aim of this research is to develop software that able to recognize Jawi character. To improve the recognition of the character, the system uses neural network training algorithm called Supervised Learning to receive new character pattern in order to strengthen the weight of the pixels. In this project, it design and train network used Radial Basis Function (RBF) with backpropagation Neural Network. This Jawi Character recognition system begins with image processing and then the output image is trained using backpropagation algorithm. Backpropagation network learns by training the input, calculating the error between the real output and target output, propagates back the error to network and modify the weight until the desired output is obtain. The system will training and recognition system will be test to ensure the system can recognize the pattern of the character

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings ( 2 )
Title notes ( 3 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Final Year Report	UMPLIB PEKAN	TK7882.P3 A95 2010 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058420
Final Year Report	UMPLIB PEKAN	CD 5386 \| TK7882.P3 A95 2010 rs Bc. (Browse shelf(Opens below))	1	Not for loan		0000058421

Project paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010

Bibliography : p. 56-57

Character recognition plays an important role in the modern world. It can solve more complex problem and makes humans’ job easier. Jawi is one of the important character that we used in our daily life. Jawi script is an important Malay heritage that has been in general, replaced by the Roman script drastically. From a dominant writing in Malay world, the usage of Jawi is confined mostly in Islamic religious context nowadays. As an initiative to encourage the learning of Jawi, this research proposed Jawi Character Recognition system using Neural Network and Supervised Learning method. The aim of this research is to develop software that able to recognize Jawi character. To improve the recognition of the character, the system uses neural network training algorithm called Supervised Learning to receive new character pattern in order to strengthen the weight of the pixels. In this project, it design and train network used Radial Basis Function (RBF) with backpropagation Neural Network. This Jawi Character recognition system begins with image processing and then the output image is trained using backpropagation algorithm. Backpropagation network learns by training the input, calculating the error between the real output and target output, propagates back the error to network and modify the weight until the desired output is obtain. The system will training and recognition system will be test to ensure the system can recognize the pattern of the character