發(fā)布時(shí)間：2018-04-26 01:10

  本文選題：表格識(shí)別 + 單元格��； 參考：《昆明理工大學(xué)》2017年碩士論文

【摘要】：目前,許多的手寫(xiě)表格信息更需要錄入、存儲(chǔ)在計(jì)算機(jī)中。在教育系統(tǒng)中,處理試卷加分表格過(guò)程中,存在著以下問(wèn)題:(1)不恰當(dāng)?shù)氖褂萌肆Y源,造成人力資源的浪費(fèi)。教育系統(tǒng)內(nèi)的工作人員很大部分是高學(xué)歷、高素質(zhì)的尖端科研人員,卻在做著這種單調(diào)而重復(fù)的工作,無(wú)疑對(duì)社會(huì)及國(guó)家造成了大量的人力資源的浪費(fèi)。(2)大量的小題加分計(jì)算會(huì)造成人員的疲勞、計(jì)算的失誤、效率低下。長(zhǎng)時(shí)間的批改試卷已經(jīng)產(chǎn)生了精神上和生理上的疲勞,這種情況下再進(jìn)行加分計(jì)算容易產(chǎn)生失誤且效率較低。本文考慮應(yīng)用表格圖像識(shí)別技術(shù)來(lái)解決教育工作者在試卷表格的加分過(guò)程中存在的問(wèn)題。為了解決以上存在的問(wèn)題,本文考慮從兩個(gè)方面進(jìn)行表格圖像的識(shí)別。一方面是表格線(xiàn)單元格的檢測(cè),一方面是表格內(nèi)數(shù)據(jù)識(shí)別。首先,查閱大量的相關(guān)文獻(xiàn),了解了表格識(shí)別相關(guān)技術(shù),分析了表格識(shí)別相關(guān)技術(shù)的國(guó)內(nèi)外的研究現(xiàn)狀,并進(jìn)行了評(píng)述。其次,本文以試卷加分表格為識(shí)別對(duì)象,針對(duì)該表格進(jìn)行了特征分析,確定了根據(jù)數(shù)據(jù)顏色的特殊性,進(jìn)行表格識(shí)別的基本思路。第三,本文應(yīng)用預(yù)處理對(duì)圖像進(jìn)行預(yù)處理,應(yīng)用直線(xiàn)檢測(cè)的方法進(jìn)行表格線(xiàn)的檢測(cè),獲得表格單元格位置情況。第四,根據(jù)顏色特殊性直接對(duì)圖像中表格內(nèi)數(shù)據(jù)進(jìn)行提取,實(shí)現(xiàn)數(shù)據(jù)圖片的切分并獲得的單個(gè)數(shù)字圖片。由于數(shù)據(jù)提取的特殊性,數(shù)據(jù)間的邊界模糊、區(qū)分不明確。本文提出了數(shù)字區(qū)域擴(kuò)散邊界界定法,實(shí)現(xiàn)每個(gè)單元格數(shù)據(jù)的切分。利用滴水算法將兩位數(shù)數(shù)據(jù)字符切分,實(shí)現(xiàn)單個(gè)數(shù)字圖片的獲得。應(yīng)用OCR技術(shù)對(duì)單數(shù)字進(jìn)行識(shí)別并計(jì)算單元格數(shù)據(jù)。最后,根據(jù)單元格位置情況,提出識(shí)別數(shù)據(jù)與單元格排序關(guān)聯(lián)算法對(duì)識(shí)別的表格數(shù)據(jù)按順存儲(chǔ)。本文利用Microsoft Visual Studio開(kāi)發(fā)平臺(tái),利用EmguCV圖片處理庫(kù),實(shí)現(xiàn)試卷加分表格識(shí)別系統(tǒng)原型的開(kāi)發(fā),并計(jì)算出總成績(jī)。驗(yàn)證出本文提出的針對(duì)具有特殊顏色表格識(shí)別的相關(guān)方法具有一定的可行性;本系統(tǒng)的開(kāi)發(fā)具有一定的使用價(jià)值。
[Abstract]:At present, many handwritten form information needs to be input, stored in the computer. In the educational system, in the process of processing the test papers and adding the score forms, there are the following problems: 1) improper use of human resources, which results in the waste of human resources. Most of the staff in the education system are highly educated and highly qualified cutting-edge researchers, but they are doing this monotonous and repetitive work. There is no doubt that a large amount of human resources is wasted to the society and the country. (2) A large number of small problems and points will cause fatigue, error in calculation and inefficiency. A long period of marking has resulted in mental and physical fatigue. In this case, the calculation of bonus points is prone to errors and low efficiency. In this paper, we consider the application of table image recognition technology to solve the problems that educators have in the process of adding scores to test papers. In order to solve the above problems, this paper considers two aspects of table image recognition. On the one hand, it is the detection of table line cells, and on the other hand, it is the data recognition in the table. Firstly, we refer to a large number of relevant literature, understand the related technology of table recognition, and analyze the current research situation of the related technology at home and abroad, and make a review. Secondly, this paper takes the test paper plus score table as the recognition object, carries on the characteristic analysis to the table, and determines the basic idea of the table recognition according to the particularity of the data color. Thirdly, the preprocessing method is used to preprocess the image, and the method of line detection is used to detect the table line, and the position of the table cell is obtained. Fourthly, the data in the table is extracted directly according to the color particularity, the segmentation of the data picture is realized and a single digital picture is obtained. Because of the particularity of data extraction, the boundary between data is fuzzy and the distinction is not clear. In this paper, a digital region diffusion boundary demarcation method is proposed to segment each cell data. Two-digit data characters are segmented by drip algorithm to obtain a single digital picture. OCR technology is used to identify single digits and calculate cell data. Finally, according to the location of the cells, the algorithm of associating the recognition data with the sorting of the cells is proposed to store the identified table data in sequence. This paper uses Microsoft Visual Studio development platform and EmguCV image processing library to realize the prototype of test paper plus score table recognition system, and calculate the total results. It is verified that the method proposed in this paper is feasible for the recognition of special color tables and the development of the system has some practical value.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP391.41

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