oalib
Search Results: 1 - 10 of 100 matches for " "
All listed articles are free for downloading (OA Articles)
Page 1 /100
Display every page Item
Handwriting Input Method Using Camera
基于摄像头的手写输入法

DENG Jun,
邓俊

计算机系统应用 , 2011,
Abstract: Handwriting input method has obvious advantage.However,current handwriting input depends on tablet.In this paper,we improve the design idea.We get an image of handwriting font shooting writing process by camera,which could get ready for recognizing character.The advantage of the handwriting input does not depend on tablet and fully use of camera which become universal.The experiments demonstrate the feasibility and usability.
De-noising Approach for Online Handwriting Character Recognition Based on Mathematical Morphology
基于数学形态学的联机手写字符识别去噪方法

SUN Yan,LIU Han-meng,RUI Jian-wu,WU Jian,
孙嫣
,刘瀚猛,芮建武,吴健

计算机科学 , 2009,
Abstract: There are lots of various noises when users are writing characters on the tablet.It's significant to eliminate these noises in order to make these characters be recognized accurately.According to the features of online handwriting characters,we analyzed all sorts of noises generated during writing on the tablet.By applying erosion,dilation,thinning operations of the mathematical morphology into pre-processing of online handwriting recognition,a de-noising approach was proposed in this article.Using appropri...
Tablet PC Support of Students' Learning Styles
Shreya Kothaneth,Ashley Robinson,Catherine Amelink
Journal of Systemics, Cybernetics and Informatics , 2012,
Abstract: In the context of rapid technology development, it comes as no surprise that technology continues to impact the educational domain, challenging traditional teaching and learning styles. This study focuses on how students with different learning styles use instructional technology, and in particular, the tablet PC, to enhance their learning experience. The VARK model was chosen as our theoretical framework as we analyzed responses of an online survey, both from a quantitative and qualitative standpoint. Results indicate that if used correctly, the tablet PC can be used across different learning styles to enrich the educational experience.
The development of a scale of attitudes toward tablet pc  [PDF]
Aykut Emre Bozdo?an,Mustafa Uzo?lu
Mevlana International Journal of Education , 2012,
Abstract: The purpose of this study is to develop a reliable and a valid scale to determine the attitudes of the primary students towards tablet pc. The items of the scale were determined by scanning the relevant literature and taking the opinions of the experts. The first draft of the scale including 49 items as a result of content reliability was applied to 434 students chosen randomly from the 7thand 8thgrades of schools in the city, city centre and the villages of Giresun in March 2012. It was revealed that the scale was clustered on single factor which consisted of 31 items and the factor loading values were 0.470 and over. Cronbach Alpha reliability coefficient was calculated to be 0.93 for the reliability of the scale.
Handwriting Recognition  [PDF]
Jayati Ghosh Dastidar,Surabhi Sarkar,Rick Punyadyuti Sinha,Kasturi Basu
Computer Science , 2015,
Abstract: This paper describes the method to recognize offline handwritten characters. A robust algorithm for handwriting segmentation is described here with the help of which individual characters can be segmented from a selected word from a paragraph of handwritten text image which is given as input.
Automatic Training Data Synthesis for Handwriting Recognition Using the Structural Crossing-Over Technique  [PDF]
Sirisak Visessenee,Sanparith Marukatat,Rachada Kongkachandra
Computer Science , 2014,
Abstract: The paper presents a novel technique called "Structural Crossing-Over" to synthesize qualified data for training machine learning-based handwriting recognition. The proposed technique can provide a greater variety of patterns of training data than the existing approaches such as elastic distortion and tangent-based affine transformation. A couple of training characters are chosen, then they are analyzed by their similar and different structures, and finally are crossed over to generate the new characters. The experiments are set to compare the performances of tangent-based affine transformation and the proposed approach in terms of the variety of generated characters and percent of recognition errors. The standard MNIST corpus including 60,000 training characters and 10,000 test characters is employed in the experiments. The proposed technique uses 1,000 characters to synthesize 60,000 characters, and then uses these data to train and test the benchmark handwriting recognition system that exploits Histogram of Gradient (HOG) as features and Support Vector Machine (SVM) as recognizer. The experimental result yields 8.06% of errors. It significantly outperforms the tangent-based affine transformation and the original MNIST training data, which are 11.74% and 16.55%, respectively.
Recognition of Handwriting from Electromyography  [PDF]
Michael Linderman, Mikhail A. Lebedev, Joseph S. Erlichman
PLOS ONE , 2009, DOI: 10.1371/journal.pone.0006791
Abstract: Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear.
Binary Validation as Segmentation for Cursive Handwriting Recognition
Hong Lee,Brijesh Verma
Asian Journal of Information Technology , 2012, DOI: 10.3923/ajit.2011.180.191
Abstract: A novel Binary Validation as Segmentation (BVS) is presented in this study. BVS is a bottom-up approach for character segmentation in off-line cursive handwriting recognition. The character segmentation is a process to extract individual character image from a handwritten word image. The extensive literature reveals that offline handwriting recognition still suffers from the absence of reliable character segmentation algorithms. The character segmentation stage is very crucial part in offline handwriting recognition because the recognition performance is directly affected by the segmentation performance. Therefore, improving the segmentation accuracy is very high prior task in this field. BVS takes over segmentation components to generate primitives. The over segmentation guarantees that none of primitives contains image pixels belonging to different characters. Based on the primitives, neighboring primitives are combined to create evaluation hypotheses. The most competent hypothesis is sought by global competency function using neural network classifier. BVS repeats cycles of combination and evaluation iteratively. Each cycle combines one a pair of two neighboring primitives permanently. That s why the proposed approach includes the term, binary. BVS also introduces Continuous Foreground Transition (CFT) model to prevent under-segmentation errors. The proposed approach has been evaluated on CEDAR benchmark database. The results showed a significant improvement in segmentation errors. The analysis of results showed that the inclusion of CFT into the validation function has played a major role in improving over segmentation and bad-segmentation errors.
Online Instructional Design Approaches Utilizing a Tablet PC
Pam Lowry
International Journal of Advanced Corporate Learning (iJAC) , 2009, DOI: 10.3991/ijac.v2i4.993
Abstract: Online students can experience what instructional strategies can be utilized using a Tablet PC in online courses. This paper summarizes how inking in Word, Powerpoint, and Windows Journal can be effective in an online course both asynchronously and synchronously. Approaches concerning assignments, discussion boards, presentations, note taking are discussed and how they can be more effective for faculty members and students using a Tablet PC. Students actually experience how a Tablet PC can be utilized in an asynchronous and synchronous environment. In summary, preliminary data will be discussed from the students and professor’s point of view and next steps. As content and assignments are being designed and developed for an online graduate course, it is important to keep in mind teaching styles, student’s learning styles, and a faculty member’s approach to promoting a Tablet PC in an online course. Even though graduate students were not required to have a Tablet PC, the course enabled them to understand how effective a Tablet PC could be in an online course whether it was delivered asynchronous or synchronously. Powerpoint presentations were created to delivery asynchronously and synchronously content to students by utilizing a Tablet PC to illustrate concepts within the presentation. Assignments were created such as evaluating e-learning products, creating a Blackboard unit, evaluating online courses, group instruction sessions, and weekly discussion boards. As these assignments were graded, comments were written on their Word and Powerpoint files using Tablet PC inking. As the Tablet PC initiative is less than one year old at Lawrence Technological University, preliminary data is being collected from faculty members and students. After this class is taught summer 2008, additional research on the efforts of course design and student learning will be explored. The Tablet PC has the potential for enhancing online course delivery.
The Effects of Handwritten Feedback on Paper and Tablet PC in Learning Japanese Writing
Kai LI,Kanji AKAHORI
International Journal of Emerging Technologies in Learning (iJET) , 2007,
Abstract: This paper compares the effect of paper-basedhandwritten feedback (PBHF) and that of Tablet PC-basedhandwritten feedback (TBHF) in learning Japanese writing.The study contributes to the research on motivation,usability and presence when learners are given differentmedia-based handwritten error feedback. The resultsindicated that there was little difference in the effect of thetwo media on motivation and usability factors. However,PBHF showed a positive effect on presence factor thanTBHF. Also, there was little difference in proficiencyimprovement after the students reviewed different mediabased handwritten feedback. The results of this studysuggest that language teachers should not use ICT withtraditional strategies, but in an innovative way to improvetheir writing instruction and enhance learners’ writingproficiency.
Page 1 /100
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.