發(fā)布時間：2018-06-15 18:28

  本文選題：漢字識別 + 字符識別　； 參考：《合肥工業(yè)大學》2017年碩士論文

【摘要】：近年來,我國快遞服務業(yè)高速發(fā)展,信息化水平不斷提高,大量的基于條形碼和二維碼的包裹自動分揀系統(tǒng)開始應用到分揀過程中。然而,快遞分揀現(xiàn)場環(huán)境復雜,條碼污損的情況時有發(fā)生。針對條碼無法讀取的包裹,快遞公司通常采用人工識別收發(fā)地址字符的方式實現(xiàn)分揀,成本較高且效率低下�；趫D像處理的漢字識別技術具有速度快,成本低,自動化程度高等優(yōu)勢,在快遞郵包分揀系統(tǒng)中擁有廣闊的應用前景。論文首先介紹了分揀系統(tǒng)的整體架構和工作原理,硬件平臺的設計和選型,并簡要敘述了軟件平臺的設計。接著根據(jù)快遞單圖像的高亮度特征,使用多閾值大津法、形態(tài)學操作和連通域篩選得到快遞單位置,并利用條碼區(qū)域的高對比度特征設計了補充定位方案。然后通過霍夫變換對圖像角度進行了修正,在多次分析投影波形后找到字符位置,并對字符圖像進行了拆分和歸一化。在字符識別階段,首先敘述了樣本字符數(shù)據(jù)庫的制作過程,然后利用像素網(wǎng)格特征和梯度方向網(wǎng)格特征對字符圖像進行特征提取,最后通過標準歐式距離分類器實現(xiàn)了字符的識別。論文最后展示了郵包分揀系統(tǒng)硬件環(huán)境搭建結(jié)果和軟件平臺開發(fā)結(jié)果,并用大量的包裹進行了驗證。實驗結(jié)果表明本系統(tǒng)字符識別準確率達到99.76%,包裹分揀準確率達到98.35%,圖像處理耗時約為0.5秒,滿足快遞包裹分揀環(huán)節(jié)的要求。使用本套系統(tǒng),可以降低人力成本,提高分揀效率,或和條碼識別技術結(jié)合,提高分揀系統(tǒng)的冗余性。
[Abstract]:In recent years, with the rapid development of express service industry in China, the level of information has been improved, a large number of parcels automatic sorting system based on bar code and two-dimensional code began to be applied to the sorting process. However, the scene of express sorting complex environment, bar code fouling occurred from time to time. For parcels that can not be read by barcode, express delivery companies usually use manual identification to send and receive address characters to achieve sorting, which is costly and inefficient. The Chinese character recognition technology based on image processing has the advantages of high speed, low cost and high degree of automation, so it has a broad application prospect in the express mail packet sorting system. This paper first introduces the whole structure and working principle of sorting system, the design and selection of hardware platform, and briefly describes the design of software platform. Then according to the high luminance feature of express single image, we use the method of multi-threshold, morphological operation and connected domain screening to get the single location of express delivery, and use the high contrast feature of bar code region to design a supplementary location scheme. Then the angle of the image is modified by Hough transform, and the character position is found after analyzing the projection waveform many times, and the character image is split and normalized. At the stage of character recognition, the process of making sample character database is described, and then the feature extraction of character image is carried out by using pixel grid feature and gradient direction grid feature. Finally, the character recognition is realized by the standard Euclidean distance classifier. At the end of the paper, the results of hardware environment and software platform development of packet sorting system are presented and verified by a large number of parcels. The experimental results show that the accuracy of character recognition is 99.76 and the accuracy of package sorting is 98.355.The processing time of image is about 0.5 seconds, which meets the requirements of the sorting link of express package. The system can reduce the labor cost, improve the sorting efficiency, or combine with the bar code recognition technology to improve the redundancy of the sorting system.
【學位授予單位】：合肥工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：F259.2;TP391.4

【相似文獻】

相關期刊論文 前10條

1 仰之;邏輯神經(jīng)網(wǎng)絡印刷體漢字識別系統(tǒng)[J];數(shù)據(jù)采集與處理;1992年04期

2 張p樦，

本文編號：2023088