【摘要】：隨著科技的快速發(fā)展和網(wǎng)絡資源的不斷豐富,電腦和手機端的教育在日常生活中越來越發(fā)揮著舉足輕重的作用。目前許多在線教育軟件可以提供題目搜索功能,用戶使用手機對題目進行拍攝,系統(tǒng)對拍攝的圖像中的文字信息進行識別與檢索,找到題庫中與拍攝內(nèi)容最接近的題目,并將答案與解答步驟反饋給用戶,或提供相似題訓練等服務�？梢娙绻軌蛘_識別出文字對于提高用戶體驗有著重要意義,而拍照下的題目照片的文本區(qū)域識別和題目類別識別的題目分類算法是圖片字符識別至關重要的一步,提高題目分類算法的準確率對于進一步的題目文本識別具有深遠的意義。為了實現(xiàn)這一目的,本文針對文本區(qū)域定位算法、分類算法、系統(tǒng)整體設計和相關應用進行了研究和實踐,具體的工作如下:1.針對文本區(qū)域定位算法的設計和實現(xiàn),本文采用了筆畫寬度變化的方法對手機拍照得到的圖像中的題目所在的文本區(qū)域進行定位,使得后續(xù)操作只針對文本區(qū)域,減少了分割與識別的工作量,提高了準確度。2.針對定位好的文本區(qū)域分類算法,本文使用提取不止一個特征的方法,對已經(jīng)定位好的區(qū)域特征進行全面的提取。然后使用從二分類支持向量機轉(zhuǎn)化而來的三分類支持向量機將文本區(qū)域分類為數(shù)學,語文,英語三種類型。3.設計和實現(xiàn)了題目字符識別系統(tǒng),鑒于光學字符識別有比較廣闊的應用前景,與此同時為了驗證前面兩種算法的有效性,設計實現(xiàn)了基于圖像字符識別的手機拍照下題目文本識別和題目數(shù)據(jù)庫檢索的系統(tǒng)。本文實現(xiàn)的兩個算法,文本區(qū)域定位算法的召回率為79.04%,筆畫準確度為79.59%,像素準確度為90.39%。準確率和運算速度優(yōu)于其他文本定位算法。定位好的文本區(qū)域分類算法可以將分類的平均準確率達到92.32%,比傳統(tǒng)分類器性能優(yōu)越。
[Abstract]:With the rapid development of science and technology and the continuous enrichment of network resources, the education of computer and mobile phone plays a more and more important role in daily life. At present, many online educational software can provide the function of subject search, users use their mobile phones to shoot the title, the system recognizes and retrieves the text information in the captured image, and finds the title closest to the shooting content in the question bank. Feedback the answer and solution steps to the user, or provide similar problem training and other services. It can be seen that if we can correctly recognize the text, it is very important to improve the user experience, and the text area recognition and the topic classification algorithm of the subject photo are the most important steps in the image character recognition. It is of great significance to improve the accuracy of topic classification algorithm for further topic text recognition. In order to achieve this goal, the text region location algorithm, classification algorithm, the overall design of the system and related applications are studied and put into practice. The specific work is as follows: 1. Aiming at the design and implementation of text region localization algorithm, this paper uses the method of stroke width change to locate the text area of the topic in the image taken by mobile phone, so that the follow-up operation is only for the text area. Reduce the workload of segmentation and recognition, improve the accuracy. 2. Aiming at the text region classification algorithm, this paper uses the method of extracting more than one feature to extract the region feature. Then the text region is classified into three types: mathematics, Chinese and English by using the three-classification support vector machine which is transformed from the two-classification support vector machine. The title character recognition system is designed and implemented. In view of the wide application prospect of optical character recognition, in order to verify the validity of the two previous algorithms, The system of subject text recognition and subject database retrieval based on image character recognition is designed and implemented. The recall rate of text region location algorithm is 79.04, the stroke accuracy is 79.59 and the pixel accuracy is 90.39. The accuracy and operation speed are better than other text location algorithms. The text region classification algorithm with good location can achieve the average accuracy of 92.32, which is superior to the traditional classifier.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41

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