【摘要】：隨著電子商務(wù)、手機(jī)支付和在線購(gòu)物等線上交易模式的發(fā)展,人們對(duì)于虛擬數(shù)據(jù)的安全性的要求越來越高,傳統(tǒng)的在線身份識(shí)別技術(shù),如賬號(hào)密碼已不能滿足安全性的需求,而生物識(shí)別技術(shù)得益于其可靠性、難偽造性開始逐漸被應(yīng)用到手機(jī)、電腦等民用電子終端設(shè)備的身份認(rèn)證和支付系統(tǒng)中。在眾多生物特征之中,視網(wǎng)膜是最可靠、最穩(wěn)定以及最難被偽造的生物特征之一,因此它非常適合作為身份認(rèn)證的標(biāo)識(shí)。在可預(yù)見的未來,視網(wǎng)膜識(shí)別技術(shù)有很大的希望被應(yīng)用到在線支付、訪問權(quán)限控制、自動(dòng)取款等對(duì)安全性需求高的民用領(lǐng)域。所以對(duì)于視網(wǎng)膜識(shí)別技術(shù)的研究有著極大的價(jià)值和良好的前景。本文深入研究了大量與視網(wǎng)膜和生物識(shí)別相關(guān)國(guó)內(nèi)外論文,特別是在視網(wǎng)膜圖像的血管分割、特征提取以及特征匹配方面。然后對(duì)這些論文提及的相關(guān)算法的進(jìn)行挑選、整合和改進(jìn),設(shè)計(jì)了一套準(zhǔn)確穩(wěn)定的視網(wǎng)膜識(shí)別方案。本文的主要工作和成果如下:(1)在視網(wǎng)膜圖像分割階段,研究了多種血管分割的算法,并加以對(duì)比。結(jié)合視網(wǎng)膜血管的特征,最后采用高斯濾波對(duì)視網(wǎng)膜血管進(jìn)行增強(qiáng),并使用最大二維熵閾值算法進(jìn)行血管分割。通過實(shí)驗(yàn)檢驗(yàn),該方法對(duì)血管分割的效果要優(yōu)于其他常用的邊緣分割算法并具有良好的抗噪性。(2)在特征點(diǎn)提取階段,根據(jù)對(duì)視網(wǎng)膜血管的研究,選用血管的分叉點(diǎn)作為特征點(diǎn),并利用形態(tài)學(xué)的知識(shí)對(duì)圖像做了細(xì)化處理。然后對(duì)Harris角點(diǎn)特征提取算法和鄰域特征提取算法作了詳細(xì)的分析,并將它們的提取結(jié)果標(biāo)注出來進(jìn)行對(duì)比,確認(rèn)領(lǐng)域特征提取為最優(yōu)的針對(duì)細(xì)化圖的提取方式。除此之外,還對(duì)利用二次特征提取來進(jìn)一步排除偽特征點(diǎn),增加了有效點(diǎn)的比例,提高了提取的準(zhǔn)確度。(3)在特征點(diǎn)匹配階段,研究和對(duì)比了幾種常用的特征匹配方法,從穩(wěn)定性、準(zhǔn)確度和效率等多個(gè)方面衡量了它們的優(yōu)缺點(diǎn)。通過分析和比較,最終設(shè)計(jì)出了一種融合算法,將三角形匹配算法和二維聚類算法結(jié)合起來,充分利用了兩者各自的優(yōu)點(diǎn),使匹配算法同時(shí)具備穩(wěn)定性和效率。除此之外還對(duì)模板三角形的選取方法和相似三角形檢索算法進(jìn)了一定的改進(jìn),提升了匹配的效率。
[Abstract]:With the development of electronic commerce, mobile phone payment and online shopping, people are demanding more and more security of virtual data. Traditional online identification technology, such as account password, can no longer meet the need of security. Because of its reliability, biometric technology has been gradually applied to the identification and payment systems of mobile phones, computers and other civil electronic terminal devices. Among the many biometric features, retina is one of the most reliable, stable and difficult to be forged, so it is very suitable for identity identification. In the foreseeable future, retinal recognition technology has great hope to be applied to online payment, access control, automatic withdrawal and other civilian areas with high security requirements. Therefore, the research of retinal recognition technology has great value and good prospects. In this paper, a large number of papers related to retina and biometrics have been deeply studied, especially in vascular segmentation, feature extraction and feature matching of retinal images. Then we select, integrate and improve the relevant algorithms mentioned in these papers, and design a set of accurate and stable retinal recognition scheme. The main work and achievements are as follows: (1) in the phase of retinal image segmentation, a variety of blood vessel segmentation algorithms are studied and compared. According to the characteristics of retinal vessels, Gao Si filter is used to enhance retinal vessels and the maximum two-dimensional entropy threshold algorithm is used to segment the retinal vessels. The experimental results show that this method is superior to other commonly used edge segmentation algorithms and has good noise resistance. (2) in the phase of feature point extraction, according to the research of retinal vessels, the bifurcation points of blood vessels are selected as feature points. The image is thinned by morphological knowledge. Then, the Harris corner feature extraction algorithm and the neighborhood feature extraction algorithm are analyzed in detail, and their extraction results are compared to confirm that the domain feature extraction is the best extraction method for thinning image. In addition, we use quadratic feature extraction to further eliminate pseudo-feature points, increase the proportion of effective points, and improve the accuracy of extraction. (3) in the phase of feature point matching, several common feature matching methods are studied and compared. Their advantages and disadvantages are measured in terms of stability, accuracy and efficiency. Through analysis and comparison, a fusion algorithm is designed, which combines triangle matching algorithm and two-dimensional clustering algorithm, and makes full use of their respective advantages, so that the matching algorithm has the stability and efficiency at the same time. In addition, the selection method of template triangle and the similar triangle retrieval algorithm are improved to improve the efficiency of matching.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：R770.4;TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 趙曉芳;林土勝;;基于結(jié)構(gòu)特征的視網(wǎng)膜血管形態(tài)識(shí)別[J];計(jì)算機(jī)工程與設(shè)計(jì);2012年03期

2 王耀貴;;圖像高斯平滑濾波分析[J];計(jì)算機(jī)與信息技術(shù);2008年08期

3 李旭超;朱善安;;圖像分割中的馬爾可夫隨機(jī)場(chǎng)方法綜述[J];中國(guó)圖象圖形學(xué)報(bào);2007年05期

4 陳波;賴劍煌;;用于圖像分割的活動(dòng)輪廓模型綜述[J];中國(guó)圖象圖形學(xué)報(bào);2007年01期

5 張鳴華;;一種聚類方法的分析[J];三明學(xué)院學(xué)報(bào);2006年02期

6 閆成新;桑農(nóng);張?zhí)煨?;基于圖論的圖像分割研究進(jìn)展[J];計(jì)算機(jī)工程與應(yīng)用;2006年05期

7 楊強(qiáng),譚禮俊;生物識(shí)別技術(shù)對(duì)比淺析[J];大眾科技;2005年02期

8 陳光新;自動(dòng)指紋識(shí)別技術(shù)及其應(yīng)用[J];江蘇船舶;2004年03期

9 馮國(guó)進(jìn),顧國(guó)華,張保民;指紋圖像預(yù)處理與特征提取[J];計(jì)算機(jī)應(yīng)用研究;2004年05期

10 朱珍,王景艷;生物識(shí)別技術(shù)與應(yīng)用[J];佛山科學(xué)技術(shù)學(xué)院學(xué)報(bào)(自然科學(xué)版);2003年03期

相關(guān)碩士學(xué)位論文 前3條

1 渠海龍;虹膜識(shí)別技術(shù)及其在身份認(rèn)證中的應(yīng)用[D];大連理工大學(xué);2012年

2 張凱;抗任意旋轉(zhuǎn)與尺度變化的圖像匹配方法研究[D];中南大學(xué);2008年

3 王君;電子商務(wù)網(wǎng)絡(luò)支付安全體系研究[D];貴州大學(xué);2007年

，

本文編號(hào)：2219868