【摘要】：網(wǎng)上閱卷相比傳統(tǒng)人工閱卷,結(jié)果更準(zhǔn)確、閱卷效率更高、閱卷過(guò)程更安全,有極大的優(yōu)勢(shì)。網(wǎng)上閱卷系統(tǒng)在上世紀(jì)90年代被提出,經(jīng)過(guò)幾十年的發(fā)展,已普遍使用在大型考試當(dāng)中。但中小型考試大多仍采用人工閱卷方式,在大型考試中也依然需要光標(biāo)閱讀機(jī)的輔助閱卷,成本非常高,后期維護(hù)困難,依賴(lài)題卡分離模式。而在題卡合一模式下則必須使用攜帶所有題目信息的復(fù)雜模板對(duì)試卷進(jìn)行解析,占用大量資源,拉長(zhǎng)了閱卷周期。另外,試卷圖像的分割大多是定區(qū)域分割,不會(huì)根據(jù)考生實(shí)際答題區(qū)域進(jìn)行智能分割。基于以上閱卷方式普遍存在的問(wèn)題,本文提出了一種基于不同題卡模式的智能閱卷系統(tǒng),對(duì)不同題卡模式分別采用不同算法對(duì)試卷進(jìn)行傾斜校正,使用精簡(jiǎn)版模板進(jìn)行定位,優(yōu)化了試卷信息的智能識(shí)別,極大內(nèi)提高了系統(tǒng)效率。主要包括以下幾個(gè)方面:(1)提出了基于不同題卡模式的兩種傾斜校正算法。一是針對(duì)大型考試中有同步頭的答題卡提出了一種新的算法,準(zhǔn)確得到了試卷圖像傾斜角度;二是針對(duì)在中小型考試中沒(méi)有任何同步頭信息的答題卡,滿(mǎn)足試卷形式的更多需求且提高了算法效率。(2)提出使用XML精簡(jiǎn)版模板進(jìn)行粗定位。省去了用DOM解析XML文件的步驟,減輕了系統(tǒng)負(fù)擔(dān)。(3)引入一維碼攜帶考生信息并對(duì)一維碼圖像進(jìn)行識(shí)別。傳統(tǒng)考試考生需要手動(dòng)填寫(xiě)個(gè)人信息效率低下,字符識(shí)別容易出錯(cuò),本文引入一維條形碼來(lái)記錄考生信息并實(shí)現(xiàn)了一維碼圖像的定位識(shí)別,簡(jiǎn)化了識(shí)別考生信息的過(guò)程,提高了識(shí)別的效率和準(zhǔn)確率。(4)優(yōu)化了客觀題的識(shí)別與分割算法。對(duì)客觀題進(jìn)行兩次分割,并用OTSU法得到閾值作為參考,比較后得到考生選項(xiàng),解決了之前的很多閱卷系統(tǒng)中客觀題閱卷只分割不識(shí)別的缺陷。(5)提出一種新的主觀題識(shí)別算法。在主觀題閱卷中提出結(jié)合了豎直方向腐蝕運(yùn)算的水平投影法,實(shí)現(xiàn)了更為智能的依據(jù)考生答題區(qū)域進(jìn)行分割的算法。由實(shí)驗(yàn)和數(shù)據(jù)結(jié)果分析得出,本文算法有效的解決了閱卷系統(tǒng)中遺留的問(wèn)題,系統(tǒng)的設(shè)計(jì)也更為靈活�？梢愿鶕�(jù)試卷類(lèi)型選擇相應(yīng)合適的傾斜校正算法并提升了算法性能。對(duì)試卷信息識(shí)別分割的相關(guān)算法進(jìn)行了優(yōu)化,進(jìn)一步智能化了閱卷過(guò)程。
[Abstract]:Compared with the traditional manual marking, the result of online marking is more accurate, the marking efficiency is higher, the marking process is more secure and has great advantages. The online marking system was put forward in the 1990s. After decades of development, it has been widely used in large-scale examinations. However, most of the small and medium-sized examinations still use manual marking method, and in large scale examination, it still needs the help of the cursor reader. The cost is very high, the maintenance is difficult in the later period, and the separation mode of the item card is relied on. However, in the mode of integration of question and card, the paper must be analyzed by using the complex template with all the subject information, which takes up a lot of resources and prolongs the marking period. In addition, test paper image segmentation is mostly fixed area segmentation, not according to the actual answer area of candidates for intelligent segmentation. Based on the above problems, this paper presents an intelligent marking system based on different card patterns, which uses different algorithms to correct the test papers, and uses a simplified template to locate the test paper. The intelligent recognition of test paper information is optimized and the system efficiency is greatly improved. The main contents are as follows: (1) two skew correction algorithms based on different problem card modes are proposed. First, a new algorithm is proposed for the answer card with synchronous head in the large scale examination, which can get the angle of the image of the test paper accurately. The second is to meet more requirements of test paper form and improve the efficiency of algorithm for the answer card without any synchronous information in the small and medium-sized examination. (2) this paper proposes the use of XML template for rough positioning. The steps of parsing XML files with DOM are saved and the system burden is lightened. (3) One-dimensional code is introduced to carry the examinee information and the one-dimensional code image is recognized. Traditional examinees need to fill in personal information manually, and character recognition is easy to make mistakes. This paper introduces one-dimensional bar code to record examinee information and realize location recognition of one-dimensional code image, which simplifies the process of identifying candidate information. The efficiency and accuracy of recognition are improved. (4) the objective problem recognition and segmentation algorithm is optimized. The objective questions are divided twice, and the threshold value obtained by OTSU method is used as a reference. After comparison, the candidates' options are obtained. It resolves the defect that the objective questions in many previous marking systems are segmented and unrecognized. (5) A new subjective problem recognition algorithm is proposed. The horizontal projection method, which combines the vertical corrosion operation, is put forward in the subjective examination paper, which realizes a more intelligent algorithm of dividing the test questions according to the examinee's answer area. The results of experiments and data analysis show that the algorithm can effectively solve the problems left over in the marking system, and the design of the system is more flexible. An appropriate skew correction algorithm can be selected according to the test paper type and the performance of the algorithm is improved. This paper optimizes the algorithm of paper information recognition and segmentation, and further intelligentizes the marking process.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：G434;TP391.41

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