本文關(guān)鍵詞： 虹膜識(shí)別 虹膜定位 特征提取 特征編碼匹配　出處：《東北石油大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：在當(dāng)代社會(huì)科技快速發(fā)展，交通通信極其便利的大環(huán)境下，身份鑒別是我們?nèi)粘Ｉ钪薪?jīng)常遇到的問(wèn)題，如何快速高效準(zhǔn)確的實(shí)現(xiàn)身份鑒別是一個(gè)火熱且極具潛力的研究課題。在眾多的生物識(shí)別算法中虹膜識(shí)別是一種新興的生物識(shí)別技術(shù)，基于虹膜來(lái)識(shí)別身份的技術(shù)具有如下幾個(gè)方面的優(yōu)勢(shì)：唯一性、穩(wěn)定性、非侵犯性以及攜帶方便等，它的這些優(yōu)勢(shì)使得基于虹膜識(shí)別在身份識(shí)別領(lǐng)域中占據(jù)著重要的位置，大量的科研學(xué)者投入無(wú)數(shù)的時(shí)間與精力到虹膜身份識(shí)別的研究中，使得虹膜識(shí)別身份的研究在這幾年得到了快速的發(fā)展。 本文研究的基于虹膜識(shí)別身份算法主要在虹膜內(nèi)外邊界點(diǎn)確定、虹膜圖像歸一化處理、虹膜圖像的特征提取與編碼以及特征編碼匹配等幾個(gè)方面進(jìn)行了學(xué)習(xí)研究，最后通過(guò)判斷特征編碼匹配度與閾值大小關(guān)系進(jìn)而實(shí)現(xiàn)身份的認(rèn)證。其中在虹膜的定位過(guò)程中，本文采用了內(nèi)外邊緣分離的虹膜圓定位算法，內(nèi)邊緣定位運(yùn)用最小二乘法圓擬合算法，考慮到內(nèi)邊緣定位精度不高的問(wèn)題，對(duì)虹膜內(nèi)邊緣運(yùn)用圓周上的差分運(yùn)算來(lái)實(shí)現(xiàn)虹膜內(nèi)邊緣的精確定位，而虹膜的外邊緣定位則運(yùn)用經(jīng)典的霍夫變換與邊緣檢測(cè)相結(jié)合算法。在歸一化階段本文采用了直角坐標(biāo)系到極坐標(biāo)的變換算法，將環(huán)形結(jié)構(gòu)虹膜圖像轉(zhuǎn)換為極坐標(biāo)下的矩形圖像，方便下階段的虹膜特征提取與識(shí)別。虹膜特征提取算法現(xiàn)階段應(yīng)用最多的是基于二維Gabor濾波器特征提取，但是由于二維Gabor濾波器寬受到限制，而一維Log Gabor濾波器能很好的克服二維Gabor的缺點(diǎn)與不足，，但是一維LogGabor在處理虹膜圖片這樣二維圖片時(shí)會(huì)丟失全局的信息，針對(duì)此種情況本文提出應(yīng)用二維的Log Gabor濾波器進(jìn)行虹膜特征提取，構(gòu)造四尺度四方向多通道Log Gabor濾波器組，利用該濾波器組對(duì)虹膜的紋理進(jìn)行特征提取并且在濾波結(jié)果中選取能夠較好的表現(xiàn)虹膜紋理的圖片進(jìn)行相位編碼。在匹配階段本文提出了最佳移位差方和距離標(biāo)準(zhǔn)偏差匹配方法，并將本文提出的算法與傳統(tǒng)的漢明距離匹配算法相比。然后應(yīng)用MATLAB的GUI模塊簡(jiǎn)單設(shè)計(jì)了虹膜身份識(shí)別界面，利用本文提出的算法對(duì)CASIA數(shù)據(jù)庫(kù)內(nèi)的虹膜圖像進(jìn)行類(lèi)內(nèi)與類(lèi)間試驗(yàn)，實(shí)驗(yàn)結(jié)果證明本文提出的最佳移位差方和距離標(biāo)準(zhǔn)偏差匹配算法具有更低的錯(cuò)誤拒絕率與錯(cuò)誤接受率，也就是本文提出的算法擁有更好的虹膜識(shí)別率，能夠取得更好的識(shí)別效果。
[Abstract]:In the great environment of the rapid development of science and technology in contemporary society and the convenience of transportation and communication, identity identification is a problem we often encounter in our daily lives. How to realize identification quickly, efficiently and accurately is a hot and potential research topic. Iris recognition is a new biometric technology in many biometric recognition algorithms. The iris recognition technology has the following advantages: uniqueness, stability, non-invasiveness and portability. These advantages make iris recognition play an important role in the field of identity recognition. A large number of researchers have invested innumerable time and energy into the research of iris identification, which has led to the rapid development of iris identification in recent years. In this paper, the iris identification algorithm based on the iris inner and outer boundary point determination, iris image normalization, iris image feature extraction and coding, and feature coding matching are studied. Finally, identity authentication is realized by judging the relationship between the matching degree of feature coding and the threshold value. In the process of iris localization, the iris circle localization algorithm with the separation of inner and outer edges is used in this paper. In the inner edge location, the least square circle fitting algorithm is used to locate the iris inner edge accurately, considering the low accuracy of the inner edge location, the difference operation on the inner iris edge is used to realize the accurate location of the iris inner edge. However, the external edge of iris is located using the classical Hough transform and edge detection algorithm. In the normalization stage, this paper adopts the transformation algorithm from rectangular coordinate system to polar coordinate system. The iris image of annular structure is converted into rectangular image in polar coordinates, which facilitates iris feature extraction and recognition in the next stage. At present, the iris feature extraction algorithm is mostly used based on two-dimensional Gabor filter. However, because the width of two-dimensional Gabor filter is limited, the one-dimensional LogGabor filter can overcome the shortcomings and shortcomings of two-dimensional Gabor well. However, one-dimensional LogGabor will lose global information when dealing with two-dimensional images such as iris images. In this paper, a two-dimensional Log Gabor filter is proposed for iris feature extraction, and a four-scale four-direction multi-channel Log Gabor filter bank is constructed. The filter bank is used to extract the feature of iris texture and to select the image which can represent the iris texture in the filtering result for phase coding. In the matching stage, we propose the best shift difference square and distance scale. Quasi-deviation matching method, The proposed algorithm is compared with the traditional hamming distance matching algorithm. Then the iris identification interface is designed by using the GUI module of MATLAB, and the Iris image in CASIA database is tested by the proposed algorithm. The experimental results show that the proposed algorithm has lower error rejection rate and error acceptance rate, that is, the proposed algorithm has better iris recognition rate. Can obtain better recognition effect.
【學(xué)位授予單位】：東北石油大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TP391.41

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 ;Moving Target Tracking Based on LogGabor Wavelet and Mean-shift Algorithm[J];Semiconductor Photonics and Technology;2009年02期

2 米林;馬亞洲;郝建軍;康洪濤;薛顯光;;一種基于Canny理論的邊緣提取改進(jìn)算法[J];重慶理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年05期

3 王春,葉虎年;虹膜識(shí)別算法的研究[J];貴州工業(yè)大學(xué)學(xué)報(bào)(自然科學(xué)版);2000年03期

4 田啟川;張潤(rùn)生;;生物特征識(shí)別綜述[J];計(jì)算機(jī)應(yīng)用研究;2009年12期

5 李晶晶;張健;;虹膜圖像內(nèi)外邊緣定位算法研究[J];通信技術(shù);2010年05期

相關(guān)博士學(xué)位論文 前2條

1 史春蕾;虹膜身份識(shí)別算法的研究[D];中國(guó)科學(xué)院研究生院（長(zhǎng)春光學(xué)精密機(jī)械與物理研究所）;2011年

2 程宇奇;用于身份鑒別的虹膜識(shí)別算法研究[D];中國(guó)科學(xué)院研究生院（長(zhǎng)春光學(xué)精密機(jī)械與物理研究所）;2010年

本文編號(hào)：1506039