一种在series60上实现三维场景绘制的方法

本文介绍了一种在vc 下,利用Hybrid公司提供的OpenGL ES的开发库和series60开发包在Series60上制作一个手机三维迷宫屏保的方法,此方法实现了嵌入式平台上的三维场景渲染。     

Exploring and exploiting a historical corpus for Arabic

This paper presents a historical Arabic corpus named HAC. At this early embryonic stage of the project, we report about the design, the architecture and some of the experiments which we have conducted on HAC. The corpus, and accordingly the search results, will be represented using a primary XML exchange format. This will serve as an intermediate exchange tool within the project and will allow the user to process the results offline using some external tools. HAC is made up of Classical Arabic texts that cover 1600 years of language use; the Quranic text, Modern Standard Arabic texts, as well as a variety of monolingual Arabic dictionaries. The development of this historical corpus assists linguists and Arabic language learners to effectively explore, understand, and discover interesting knowledge hidden in millions of instances of language use. We used techniques from the field of natural language processing to process the data and a graph-based representation for the corpus. We provided researchers with an export facility to render further linguistic analysis possible.     

基于OpenGL的分形山三维模拟生成技术

采用OpenGL技术与VC 6.0结合分形几何的方法来模拟绘制三维分形山。利用分形几何理论建立几何模型;依据分形插值理论设计相应的算法,得到模拟对象的几何数据,绘制出三维山和云的图形;利用OpenGL的图形处理及渲染功能对生成的图形进行色彩、光照、纹理等方面的处理,得到三维分形山的模拟图形。     

交互式数据可视化软件开发系统的设计与实现

ＩＤＶＴ１．０是运行于ＰＣ平台的交互式数据可视化软件开发系统,其核心是用于绘制科学计算数据、商业统计图形、多边形模型的对象库。使用ＩＤＶＴ１．０,程序员可以快速开发交互式数据可视化应用软件。该文论述ＩＤＶＴ １．０的系统设计与实现：（１）对象的内存管理;（２）三维交互设计;（３）三维坐标的数据标注。     

Improving Accuracy of Spam Detection

Many algorithms have been implemented for the problem of document categorization. The majority work in this area was achieved for English text, while a very few approaches have been introduced for the Arabic text. The nature of Arabic text is different from that of the English text and the preprocessing of the Arabic text is more challenging. This is due to Arabic language is a highly inflectional and derivational language that makes document mining a hard and complex task. In this paper, we present an Auto...     

Region growing based segmentation algorithm for typewritten and handwritten text recognition

This paper presents a new technique of high accuracy to recognize both typewritten and handwritten English and Arabic texts without thinning. After segmenting the text into lines (horizontal segmentation) and the lines into words, it separates the word into its letters. Separating a text line (row) into words and a word into letters is performed by using the region growing technique (implicit segmentation) on the basis of three essential lines in a text row. This saves time as there is no need to skeletonize or to physically isolate letters from the tested word whilst the input data involves only the basic information—the scanned text. The baseline is detected, the word contour is defined and the word is implicitly segmented into its letters according to a novel algorithm described in the paper. The extracted letter with its dots is used as one unit in the system of recognition. It is resized into a 9 × 9 matrix following bilinear interpolation after applying a lowpass filter to reduce aliasing. Then the elements are scaled to the interval [0,1]. The resulting array is considered as the input to the designed neural network. For typewritten texts, three types of Arabic letter fonts are used—Arial, Arabic Transparent and Simplified Arabic. The results showed an average recognition success rate of 93% for Arabic typewriting. This segmentation approach has also found its application in handwritten text where words are classified with a relatively high recognition rate for both Arabic and English languages. The experiments were performed in MATLAB and have shown promising results that can be a good base for further analysis and considerations of Arabic and other cursive language text recognition as well as English handwritten texts. For English handwritten classification, a success rate of about 80% in average was achieved while for Arabic handwritten text, the algorithm performance was successful in about 90%. The recent results have shown increasing success for both Arabic and English texts.     

Improving mobile multi-tap text entry for Arabic language

Classical mobile phone keypads which consist of 12 buttons are commonly used to write short text messages through two common methods, the multi-tap and the predictive text entry. For the Arabic language mobile keypads, all Arabic letters are distributed over the 8 buttons of the keypad where three or more letters share the same button. In this paper, a new text entry environment is proposed. The environment includes two proposed improved approaches for Arabic language messages to make the multi-tap text entry method faster and easier. The first approach is based on the idea of remapping the distribution of Arabic letters on the keypad according to the frequency of letters. In the second approach, a bi-Gram based method is used to predict the next letter to be typed automatically. The proposed approaches are evaluated using a corpus of 1514 real Arabic text messages. Several experiments were conducted to evaluate the proposed text entry environment. The results of the experiments have showed that using the proposed remapped keypad is faster and consumes less effort in comparison to the classical keypad.     

OpenGL图像处理管线研究及实现

OpenGL是国际上通用的编程接口,主要通过颜色缓冲区读出和写入图像数据。论文研究了利用OpenGL的图像处理管线把图像数据直接从颜色缓冲区读取到内存缓冲区,并在内存缓冲区对图像进行操纵,以及在图像的读取和写入操作时自动应用的图像操作方法。实验表明,利用OpenGL图像处理管线进行图像渲染可以大大提高渲染性能。     

Utilizing pseudo-spaces to improve Arabic text steganography for multimedia data communications

Steganography is used for multimedia data security. It is a process of hiding the data within multimedia communication between the parties embedding the secret data inside a carrier file to be protected during its transmission. The research focus is on hiding within Arabic text steganography as a current challenging research area. The work innovation is utilizing text pseudo-spaces characters for data hiding. We present two studies for this text Steganography utilizing pseudo-spaces alone as well as combined with Kashida (extension character) as the old Arabic text stego techniques. Experimental results have shown that the proposed algorithms achieved high capacity and security ratio as compared to state-of-the-art Steganography methods presented for Arabic language. The proposed pseudo-spaces stego technique is of great benefit that can be further used for languages similar to Arabic such as Urdu and Persian as well as opening direction of text-stego research for other languages of the world.

     

Development of universal environment for constructing 5-axis virtual machine tool based on modified D–H notation and OpenGL

For construction of a universal 5-axis virtual machine simulation system, a new methodology is proposed in this paper. The OpenGL library is used to render the virtual environment and to display all motions of the virtual machine tool. In order to achieve the universal construction procedures, the D–H notation is adopted. The user interfaces are developed to help users to select the configuration of machine tool. Once the configuration is decided, the motion directions between adjacent links are known and the kinematic parameters are described by D–H notation. Then the post-processor is derived by D–H notation. Finally, the motion control simulation of the virtual machine tool is executed by D–H transformation matrix. This new methodology can assist developers in constructing the simulation system for the universal 5-axis virtual machine tool efficiently and effectively.     

ViStA: a visualization system for exploring Arabic text

Text visualization has become a significant tool that facilitates knowledge discovery and insightful presentation of large amounts of data. This paper presents a visualization system for exploring Arabic text called ViStA. We report about the design, the implementation and some of the experiments we conducted on the system. The development of such tools assists Arabic language analysts to effectively explore, understand, and discover interesting knowledge hidden in text data. We used statistical techniques from the field of Information Retrieval to identify the relevant documents coupled with sophisticated natural language processing (NLP) tools to process the text. For text visualization, the system used a hybrid approach combining latent semantic indexing for feature selection and multidimensional scaling for dimensionality reduction. Initial results confirm the viability of using this approach to tackle the problem of Arabic text visualization and other Arabic NLP applications.     

A frame-based approach for capturing semantics from Arabic text for text-to-sign language MT

This paper describes the design and implementation of a computational model for Arabic natural language semantics, a semantic parser for capturing the deep semantic representation of Arabic text. The parser represents a major part of an Interlingua-based machine translation system for translating Arabic text into Sign Language. The parser follows a frame-based analysis to capture the overall meaning of Arabic text into a formal representation suitable for NLP applications that need for deep semantics representation, such as language generation and machine translation. We will show the representational power of this theory for the semantic analysis of texts in Arabic, a language which differs substantially from English in several ways. We will also show that the integration of WordNet and FrameNet in a single unified knowledge resource can improve disambiguation accuracy. Furthermore, we will propose a rule based algorithm to generate an equivalent Arabic FrameNet, using a lexical resource alignment of FrameNet1.3 LUs and WordNet3.0 synsets for English Language. A pilot study of motion and location verbs was carried out in order to test our system. Our corpus is made up of more than 2000 Arabic sentences in the domain of motion events collected from Algerian first level educational Arabic books and other relevant Arabic corpora.     

Comparative evaluation of text classification techniques using a large diverse Arabic dataset

A vast amount of valuable human knowledge is recorded in documents. The rapid growth in the number of machine-readable documents for public or private access necessitates the use of automatic text classification. While a lot of effort has been put into Western languages—mostly English—minimal experimentation has been done with Arabic. This paper presents, first, an up-to-date review of the work done in the field of Arabic text classification and, second, a large and diverse dataset that can be used for benchmarking Arabic text classification algorithms. The different techniques derived from the literature review are illustrated by their application to the proposed dataset. The results of various feature selections, weighting methods, and classification algorithms show, on average, the superiority of support vector machine, followed by the decision tree algorithm (C4.5) and Naïve Bayes. The best classification accuracy was 97 % for the Islamic Topics dataset, and the least accurate was 61 % for the Arabic Poems dataset.     

OpenGL视类及其在三维图形开发中的应用

ＯｐｅｎＧＬ是一个功能强大的三维图形库,然而在使用 ＭＦＣ开发应用程序并采用 ＯｐｅｎＧＬ绘制 Ｍ维 图形的时候,必须遵循一些固定的规范：先建立ＯｐｅｎＧＬ绘制环境,然后才能使用ＯｐｅｎＧＬ命令。本 文介绍了一个基于ＭＦＣ的具有封装性、可继承性和可重用的ＯＰｅｎＧＬ视类,并给出该视类的具体 实现方法。我们将这个 ＯｐｅｎＧＬ视类应用于分形三维重建软件的开发中,有效地缩短了开发周期。     

基于统计模型的海水运动仿真

人们常用建立物理模型的方式来达到模拟自然现象,然后通过OpenGL绘制出来;同时OpenGL本身也有用于模拟自然现象的粒子系统。对海水的模拟通常通过建立海水动力学模型来达到,而该文介绍通过建立统计模型的方式来模拟自然现象,提出了通过建立统计模型来模拟海水的运动的方法,并对其加以实现。     

OpenGL ES 1.1 implementation based on OpenGL

In this paper, we present an efficient way of implementing OpenGL ES 1.1 3D graphics API library for the environments with hardware-supported OpenGL facility, typically as desktop PCs. Although OpenGL ES was started from the existing OpenGL features, it rapidly became the standard 3D graphics library customized for embedded systems through introducing fixed-point arithmetic operations, buffer management with fixed-point data type supports, completely new texture mapping functions and others. Currently, it is the official 3D graphics API for Google Android, Apple iPhone, Sony PlayStation3, etc. In this paper, we achieved improvements on the arithmetic operations for the fixed-point number representation, which is the most characteristic data type for OpenGL ES 1.1. For the conversion of fixed-point data types to the floating-point number representations for the underlying OpenGL, we show the way of efficient conversion processes even with satisfying OpenGL ES standard requirements. We also introduced a specialized memory management scheme to manage the converted data from the buffer containing fixed-point numbers. In the case of texture processing, the requirements in both standards are quite different, and thus we used completely new software-implementations. Our final implementation of OpenGL ES library provides all of more than 200 functions in the standard specification and passed its conformance test, to show its compliance with the standard. From the efficiency point of view, we measured its execution times for several OpenGL ES-specific application programs and achieved remarkable improvements.     

KHATT: An open Arabic offline handwritten text database

A comprehensive Arabic handwritten text database is an essential resource for Arabic handwritten text recognition research. This is especially true due to the lack of such database for Arabic handwritten text. In this paper, we report our comprehensive Arabic offline Handwritten Text database (KHATT) consisting of 1000 handwritten forms written by 1000 distinct writers from different countries. The forms were scanned at 200, 300, and 600 dpi resolutions. The database contains 2000 randomly selected paragraphs from 46 sources, 2000 minimal text paragraph covering all the shapes of Arabic characters, and optionally written paragraphs on open subjects. The 2000 random text paragraphs consist of 9327 lines. The database forms were randomly divided into 70%, 15%, and 15% sets for training, testing, and verification, respectively. This enables researchers to use the database and compare their results. A formal verification procedure is implemented to align the handwritten text with its ground truth at the form, paragraph and line levels. The verified ground truth database contains meta-data describing the written text at the page, paragraph, and line levels in text and XML formats. Tools to extract paragraphs from pages and segment paragraphs into lines are developed. In addition we are presenting our experimental results on the database using two classifiers, viz. Hidden Markov Models (HMM) and our novel syntactic classifier.     

Extracting text from scanned Arabic books: a large-scale benchmark dataset and a fine-tuned Faster-R-CNN model

Datasets of documents in Arabic are urgently needed to promote computer vision and natural language processing research that addresses the specifics of the language. Unfortunately, publicly available Arabic datasets are limited in size and restricted to certain document domains. This paper presents the release of BE-Arabic-9K, a dataset of more than 9000 high-quality scanned images from over 700 Arabic books. Among these, 1500 images have been manually segmented into regions and labeled by their functionality. BE-Arabic-9K includes book pages with a wide variety of complex layouts and page contents, making it suitable for various document layout analysis and text recognition research tasks. The paper also presents a page layout segmentation and text extraction baseline model based on fine-tuned Faster R-CNN structure (FFRA). This baseline model yields cross-validation results with an average accuracy of 99.4% and F1 score of 99.1% for text versus non-text block classification on 1500 annotated images of BE-Arabic-9K. These results are remarkably better than those of the state-of-the-art Arabic book page segmentation system ECDP. FFRA also outperforms three other prior systems when tested on a competition benchmark dataset, making it an outstanding baseline model to challenge.