IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE) e-ISSN: 2278-1676,p-ISSN: 2320-3331, Volume 10, Issue 2 Ver. II (Mar – Apr. 2015), PP 19-30 www.iosrjournals.org DOI: 10.9790/1676-10221930 www.iosrjournals.org 19 | Page 3D-Discrete Wavelet and Multiwavelet Transform Based on Recognition System Design ofLatin Handwritten Text Features Extraction Laith Ali Abdul-Rahaim Electrical Engineering Department, Babylon University, Babil, Iraq Abstract:Handwriting recognition is a wayto knowthe letters or words are present in handwritten text. This technique is very important to communication between man and machine and can help in handwritten documentsprocessing automatically. It is a part of the Optical Character Recognition (OCR), thatdeal with machine-print only.The proposed system is a character-based recognition and it is a writer independent system. The recognition responsibility of the proposed system is for 52 character classes [uppercases (A-Z) and the lowercases (a-z)]. The suggested system includes the essential stages needed for most of the pattern recognition systems. These stages are the preprocessing stage, the features extraction stage, the pattern matching and classification stage and the postprocessing stage. The proposed methods employ threeDimensional Discrete Multiwavelet transform Critically Sampledand also three Dimensional Discrete Wavelet transform (3D- DMWTCS, DWT)using multiresolution image decomposition techniques working together with multiple classification methods as a powerful classifier. The classification stage is designed by using a minimum distance classifier depending on Euclidean Distance which has a high speed performance. The system design also includes a modest postprocessing stage that makes a consistency between the recognized characters within the same word in relation to their upper and lower cases. Theoverallclassification accuracy of proposed systemscan be obtained are 95.76 percent with 3D-DMWTCS and 94.05percent with 3D-DWT based on the Rimes database. Key word: 3D-DMWTCS, 3D-DWT, dpi, HWR, RR, OCR, ED, MDC. I. Basic Concepts ofthe Handwriting Recognition Handwriting(HW) is one of the most important methods of communication used by civilized peoples. It is used for both personal (e.g. letters, notes, addresses on envelopes, etc.) and business communications (e.g. bank cheques, business forms, etc.). The writing is a physical process where the brain sends an order through the nervous system to the arm, hand and fingers, where together they manipulate the writing tool. Therefore, a person’s handwriting is as unique as human fingerprints and facial features. However, it varies depending upon many factors (age, education, temper, left or right handed writer, etc.).With the emergence of computer, it became possible that the machines can also reduce the amount of mental work required for many tasks. One of these tasks is the recognition of human handwriting. Of course, significant progress in the way of handwriting recognition computer has been, but the computer will not be able to read human handwriting as well as a human being. Even so, it does not hurt to try to develop technology that can approach the ability to recognize of humans. Since the handwriting is very important that allow people communicate each other, it is important to found an easy way tointeractive with thecomputer [1, 2]. Handwriting recognition (HWR) system can be ―on- line‖ or ―off-line‖. It is ―online‖ when pressed by the pen on the personal data assistants' electronic (PDA) devices screen where they are pressed account pen and indicate immediately on screen. It is ―off-line‖ when it is useda previously written text, such as any image scanned by a scanner. The on-line problem is usually easier than the off-line problem since more information is available. So far, most of the off-line handwriting recognition systems are applied to reading letters, postal addresses and then automatic sorting of postal mail, processing forms like bank cheques or discrimination of the different scripts for individual writers (Handwriting identification) [3]. II. Model for off-lineHandwriting Recognition Handwriting Recognition HWR is interpretation of data which describes handwritten objects to generate a description of that interpretation in a desired format. Or in other words it is a determination what characters or words are existent in the image of text have handwritten words or characters. The significant benefit of HWR system was in communication between man and machine and convertsthe handwritten documents image to understand from the machine. And use a wide range of techniques to perform off-line handwriting recognition. To transform this image to understandable information by computers requires solving a