本文選題：嵌入式平臺 + 閱讀輔助　； 參考：《華東師范大學(xué)》2017年碩士論文

【摘要】：在現(xiàn)實生活中,文字作為信息的主要載體形式之一,承載著人類文明,向人們傳播知識,弘揚文化,記錄歷史。隨著電子信息技術(shù)的發(fā)展,出現(xiàn)了一維碼、二維碼以及彩色條形碼等能夠包含較多信息的條碼圖像作為信息載體,其中二維條碼是主要的信息載體。然而,對于盲人和弱視力者而言,在獲取文本信息或條形碼信息時,仍存在諸多不便。這是因為目前市面上大多數(shù)文字識別或者條形碼識別的工具是智能手機(jī)端的APP,使用時需要打開APP,并將攝像頭對準(zhǔn)文本區(qū)域或者條碼區(qū)域。對于盲人和弱視力者而言,使用難度較高,且多數(shù)智能手機(jī)APP的識別結(jié)果仍是以文本的形式呈獻(xiàn)給用戶,所以并沒有從根本上解決盲人和弱視力群體的閱讀問題。因此,研究一款專門為盲人和弱視力者進(jìn)行閱讀輔助的設(shè)備就顯得非常必要。本文旨在融合現(xiàn)有的可穿戴設(shè)備理念,設(shè)計一款專門為方便盲人和弱視力者使用的可穿戴閱讀輔助系統(tǒng),在研究和比對現(xiàn)有的文字識別或條碼識別產(chǎn)品的基礎(chǔ)上,對其功能和實現(xiàn)平臺進(jìn)行改進(jìn),結(jié)合無線網(wǎng)絡(luò),設(shè)計一款能實現(xiàn)文字識別和二維碼識別的可穿戴設(shè)備,為盲人和弱視力者進(jìn)行閱讀輔助。本文主要工作內(nèi)容及創(chuàng)新點如下:1、提出一種在資源相對較少的嵌入式平臺下實現(xiàn)二維碼譯碼的方法。通過本文選擇的芯片所特有的位帶存儲區(qū)以及DMA(直接內(nèi)存訪問)雙緩沖機(jī)制,快速完成圖像采集、二值化和壓縮存儲;提出使用連通邊界跟蹤算法尋找二維碼定位符,減少大量浮點運算;不對圖像進(jìn)行旋轉(zhuǎn),直接在當(dāng)前旋轉(zhuǎn)角度上進(jìn)行采樣,進(jìn)而獲取二維碼比特流信息,實現(xiàn)二維碼在資源相對較少的嵌入式平臺下的譯碼。2、通過提取圖像中各像素筆畫寬度特征檢測圖像中的文本區(qū)域,較大程度地保留文本區(qū)域原始信息,檢測效果較好。3、根據(jù)不同語言的字符差異,分析并提出利用字符分割時得到的最小外接矩形高度與寬度的比值、字符筆畫寬度和字符間距等特點區(qū)分不同語言字符。4、使用半監(jiān)督學(xué)習(xí)方式訓(xùn)練神經(jīng)網(wǎng)絡(luò)識別英文和阿拉伯?dāng)?shù)字,用Tesseract-OCR開源引擎識別中文簡體漢字。實驗發(fā)現(xiàn),半監(jiān)督學(xué)習(xí)算法訓(xùn)練英文字母和阿拉伯?dāng)?shù)字所花的時間較長,但訓(xùn)練好后,識別效果較準(zhǔn),速度較快;Tesseract-OCR也具有較好的漢字識別效果。5、設(shè)計了一款小體積、低成本的嵌入式可穿戴閱讀輔助設(shè)備。在資源相對較少的嵌入式平臺上實現(xiàn)圖像識別、網(wǎng)絡(luò)通信、語音朗讀等功能。具體實現(xiàn)的功能主要包括,在嵌入式平臺上實現(xiàn)二維碼離線譯碼;通過無線網(wǎng)絡(luò),在服務(wù)器端實現(xiàn)文字在線識別。將嵌入式平臺下二維碼譯碼結(jié)果語音朗讀給盲人或者弱視力使用者,也可將服務(wù)器端文字識別結(jié)果的GB2312編碼通過無線網(wǎng)絡(luò)發(fā)送至嵌入式平臺的語音模塊朗讀。硬件設(shè)計上充分考慮設(shè)備的可穿戴性、低功耗、散熱性等問題,設(shè)計出外觀與手表相近的可穿戴設(shè)備,盲人和弱視力使用者僅需要通過簡單的屏幕觸摸即可閱讀文字或識別二維碼。本文所設(shè)計的可穿戴式閱讀輔助系統(tǒng),達(dá)到了成本較低,識別率較好,使用方便的效果。既方便盲人和弱視力的人閱讀文獻(xiàn)和二維條碼,也方便語言學(xué)習(xí)者,兒童等人群的使用。部分代碼和硬件設(shè)計方案已發(fā)布和托管到GitHub上。
[Abstract]:In real life, text is one of the main forms of information, carrying human civilization, spreading knowledge, carrying forward culture and recording history. With the development of electronic information technology, a bar code image, such as one dimension code, two-dimensional code and color bar code, which can contain more information, is used as the information carrier, in which two dimensional bar code is used. However, for the blind and weak eyesight, there is still a lot of inconvenience in obtaining text information or bar code information. This is because most of the text recognition or bar code identification tools on the market are APP on the smartphone end, and when they are used, the APP should be opened and the camera is directed to the text area or the text area. Bar code area. For the blind and weak eyesight, it is difficult to use, and the recognition results of most smart phone APP are still presented to the user in the form of text, so there is no fundamental solution to the reading problems of the blind and weak eyesight groups. Therefore, the study of a device for reading auxiliary for the blind and weak eyesight people is to be studied. The purpose of this paper is to integrate the existing wearable device concept and design a wearable reading assistant system for the convenience of the blind and weak eyesight. Based on the research and comparison of the existing text recognition or barcode recognition products, the function and implementation platform are improved, and a wireless network is designed to design a model. The wearable device that can realize word recognition and two-dimensional code recognition can be used for reading for the blind and weak eyesight. The main contents and innovations of this paper are as follows: 1, a method for the realization of two-dimensional code decoding is proposed in the embedded platform with relatively few resources. In memory access) double buffering mechanism, the image acquisition, two value and compression storage are completed quickly, and a connected boundary tracking algorithm is used to find two-dimensional code locator and reduce a large number of floating-point operations. The decoding.2 under the relatively small embedded platform is used to detect the text area in the image by extracting the feature of each pixel's stroke width in the image. The original information of the text area is preserved to a great extent, and the detection effect is better.3. According to the character difference of different languages, the minimum outer rectangular height obtained by the character segmentation is analyzed and proposed. The ratio of width, character stroke width and character spacing distinguish different language characters.4, use semi supervised learning method to train neural network to recognize English and Arabia numbers, and use Tesseract-OCR open source engine to identify Chinese Simplified Chinese characters. Experiments show that the time spent by semi supervised learning algorithm training English letters and Arabia numbers Long, but after training, the recognition effect is more accurate and the speed is faster; Tesseract-OCR also has a good Chinese character recognition effect.5. A small, low cost embedded wearable reading assistant is designed. The functions of image recognition, network communication and voice reading are realized on the embedded platform with relatively few resources. It mainly includes the off-line decoding of two-dimensional code on the embedded platform; the text online recognition is realized on the server side through the wireless network. The two dimensional code decoding results under the embedded platform are read aloud to the blind or weak eyesight users, and the GB2312 encoding of the server end recognition result can be sent to the embedded system through the wireless network. The hardware design takes full account of the wearability, low power consumption and heat dissipation of the equipment, and designs a wearable device with similar appearance to the watch. The blind and weak eyesight users only need to read the text or identify the two-dimensional code through a simple screen touch. The wearable reading assistance designed in this article is designed. The system has achieved a lower cost, better recognition rate and convenient use. It is convenient for the blind and weak eyesight to read the literature and two-dimensional bar code, and also facilitates the use of language learners and children. Part of the code and hardware design has been published and hosted on GitHub.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP391.4;TP368.33

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 鐘陽;李外云;金豫;;一種基于CIS的二維碼掃描識別算法[J];信息技術(shù);2016年12期

2 吳兆林;;基于Zbar條形碼圖像識別的實現(xiàn)[J];數(shù)字技術(shù)與應(yīng)用;2016年08期

3 任紅格;李冬梅;李福進(jìn);;基于半監(jiān)督學(xué)習(xí)的動態(tài)神經(jīng)網(wǎng)絡(luò)結(jié)構(gòu)設(shè)計[J];計算機(jī)應(yīng)用;2016年03期

4 蘇宏鋒;王華;李瑛;祝良;;FPGA核心控制板的PCB散熱設(shè)計[J];電子世界;2016年03期

5 鐘陽;李外云;金豫;;基于圖像識別的智能文字閱讀系統(tǒng)[J];數(shù)字技術(shù)與應(yīng)用;2016年01期

6 方華;郭靜;田敬北;;基于OpenCV的嵌入式圖像處理平臺的構(gòu)建[J];無線互聯(lián)科技;2015年03期

7 余維克;黎福海;;一種基于ADI低成本DSP實現(xiàn)的QR碼識別系統(tǒng)[J];電子技術(shù)應(yīng)用;2013年04期

8 李秀英;袁紅;;幾種圖像縮放算法的研究[J];現(xiàn)代電子技術(shù);2012年05期

9 孫華;張航;;漢字識別方法綜述[J];計算機(jī)工程;2010年20期

10 韋佳;彭宏;;基于局部與全局保持的半監(jiān)督維數(shù)約減方法[J];軟件學(xué)報;2008年11期

相關(guān)博士學(xué)位論文 前1條

1 李響;嵌入式圖像信息處理系統(tǒng)的核心算法研究與系統(tǒng)實現(xiàn)[D];浙江大學(xué);2012年

相關(guān)碩士學(xué)位論文 前10條

1 阮翔;基于改進(jìn)的BP神經(jīng)網(wǎng)絡(luò)庫存預(yù)測模型及其應(yīng)用研究[D];南昌航空大學(xué);2016年

2 徐浩然;基于Harris角點的網(wǎng)絡(luò)視頻中文本區(qū)域檢測方法的研究[D];吉林大學(xué);2016年

3 李敏強;自然場景維吾爾文本區(qū)域檢測[D];新疆大學(xué);2015年

4 劉華水;電子電路熱分析研究[D];南京大學(xué);2015年

5 盧小玲;基于半監(jiān)督學(xué)習(xí)的人臉識別算法研究[D];電子科技大學(xué);2015年

6 程育恒;基于Tesseract開源OCR引擎的證件識別系統(tǒng)的設(shè)計與實現(xiàn)[D];東華大學(xué);2014年

7 姚東林;基于安卓的文字識別系統(tǒng)的設(shè)計與實現(xiàn)[D];西安電子科技大學(xué);2014年

8 惠新明;基于μC/OS-Ⅱ和LwIP的嵌入式網(wǎng)關(guān)研究與實現(xiàn)[D];西安電子科技大學(xué);2014年

9 張文杰;基于移動終端的報紙版面分析及識別[D];北京郵電大學(xué);2014年

10 龍清清;基于二維碼識別的Android智能手機(jī)導(dǎo)游系統(tǒng)研究[D];中國計量學(xué)院;2013年

，

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