【摘要】：近年來，觸屏的普及大大推進(jìn)手寫交互的應(yīng)用，手寫識(shí)別技術(shù)日顯其價(jià)值。同時(shí)，行業(yè)信息化建設(shè)的進(jìn)程開始面臨大數(shù)據(jù)的挑戰(zhàn)，包括了數(shù)據(jù)的運(yùn)維、數(shù)據(jù)資源的重分配、數(shù)據(jù)向業(yè)務(wù)價(jià)值的轉(zhuǎn)化等，，從而產(chǎn)生了行業(yè)云理念。商業(yè)和學(xué)術(shù)界的許多行業(yè)都面臨著這樣的調(diào)整，本文所研究的手寫識(shí)別領(lǐng)域也同樣面臨行業(yè)大數(shù)據(jù)的機(jī)遇和挑戰(zhàn)。因此，本文針對(duì)手寫識(shí)別研究領(lǐng)域，提出一種行業(yè)云的解決方案。 本文提出了基于開源云計(jì)算平臺(tái)OpenStack IaaS層構(gòu)建的手寫識(shí)別數(shù)據(jù)即服務(wù)云平臺(tái)（Handwriting Recognition Data Platform as a Service，簡(jiǎn)稱：HRDPaaS）。其目的和意義在于為解決手寫識(shí)別當(dāng)前遇到的問題提供合理的方案：1）低配置端（如嵌入式、Web端）的手寫識(shí)別難以實(shí)現(xiàn)；2）個(gè)性化的手寫識(shí)別運(yùn)算復(fù)雜，需要大存儲(chǔ)、高配置；3）手寫識(shí)別研究所需的樣本集成本很高、數(shù)量很大；4）該領(lǐng)域數(shù)據(jù)資源不均衡、數(shù)據(jù)服務(wù)缺失。 本文所提出的平臺(tái)針對(duì)手寫識(shí)別的技術(shù)領(lǐng)域，以手寫數(shù)據(jù)為核心，開放手寫筆跡識(shí)別服務(wù)、手寫數(shù)據(jù)統(tǒng)計(jì)服務(wù)、手寫樣本調(diào)度服務(wù)、數(shù)據(jù)可視化服務(wù)等。同時(shí)對(duì)接平臺(tái)基礎(chǔ)資源監(jiān)控系統(tǒng)以及數(shù)據(jù)運(yùn)維系統(tǒng)，利用基于OpenStack的彈性伸縮、負(fù)載均衡等解決方案，實(shí)現(xiàn)平臺(tái)計(jì)算資源的部署和調(diào)度。 本研究課題實(shí)現(xiàn)的系統(tǒng)和服務(wù)包括：1）在線手寫識(shí)別，拓寬了手寫交互的應(yīng)用場(chǎng)合；2）大量用戶的海量數(shù)據(jù)存儲(chǔ)，為個(gè)性化手寫識(shí)別的研究提供數(shù)據(jù)基礎(chǔ)；3）提供大量的樣本調(diào)度，降低手寫識(shí)別研究的成本；4）整合了海量具有自然語義的樣本集，為手寫樣本數(shù)據(jù)向語義的轉(zhuǎn)化提供基礎(chǔ)。利用該平臺(tái)，可以通過數(shù)據(jù)，整合、優(yōu)化、重組手寫交互應(yīng)用和研發(fā)的生態(tài)鏈。
[Abstract]:In recent years, the popularity of touch screen has greatly promoted the application of handwritten interaction, and handwriting recognition technology is becoming more and more valuable. At the same time, the process of the construction of industry information began to face the challenge of big data, including the operation and maintenance of data, the redistribution of data resources, the transformation of data to business value, and so on, which resulted in the concept of industry cloud. Many industries in business and academia are facing such adjustment. The handwritten recognition field studied in this paper also faces the opportunities and challenges of industry big data. Therefore, this paper proposes a solution of industry cloud for handwritten recognition. This paper proposes a handwritten recognition data called Service Cloud platform (Handwriting Recognition Data Platform as a Service,) based on the open source cloud computing platform (OpenStack IaaS layer). Its purpose and significance is to provide a reasonable scheme for solving the current problems encountered in handwriting recognition: 1) it is difficult to realize handwriting recognition in low configuration terminal (such as embedded web side). 2) the operation of personalized handwriting recognition is complex, which needs large storage and high configuration. 3) the cost of the sample set is very high and the quantity is very large. 4) the data resource in this field is unbalanced and the data service is missing. Aiming at the technical field of handwritten recognition, the platform proposed in this paper is based on handwritten data, and open handwritten handwriting recognition service, handwritten data statistic service, handwritten sample scheduling service, data visualization service and so on. At the same time, the basic resource monitoring system and the data operation and maintenance system of the platform are docked to realize the deployment and scheduling of the platform computing resources by using the solutions of elastic expansion and load balancing based on OpenStack. The system and service implemented in this research include: 1) online handwriting recognition, which broadens the application of handwritten interaction and broadens the mass data storage of a large number of users, and provides a data basis for the study of personalized handwriting recognition. 3) providing a large number of samples scheduling and reducing the cost of handwritten recognition. 4) integrating a large number of samples with natural semantics to provide the basis for the transformation of handwritten sample data to semantics. With this platform, the ecological chain of handwritten interactive applications and R & D can be reorganized through data, integration, optimization and reorganization.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP391.41;TP393.09

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本文編號(hào)：2159770