本文選題：虹膜識(shí)別 + 特征穩(wěn)定性　； 參考：《河南科技大學(xué)》2017年碩士論文

【摘要】：隨著我國信息化技術(shù)的深入發(fā)展,信息安全日益成為社會(huì)關(guān)注的重要問題。生物特征識(shí)別技術(shù)由于自身具有的重要特性,已被廣泛的關(guān)注和應(yīng)用,其中虹膜識(shí)別技術(shù)由于自身的特點(diǎn)(高度準(zhǔn)確性、唯一性、穩(wěn)定性、防偽性和非接觸性)而被認(rèn)為是一種具有高度研究價(jià)值和應(yīng)用前景的生物識(shí)別技術(shù)。然而在實(shí)際的應(yīng)用中,虹膜識(shí)別技術(shù)還存在著很多的缺陷,如低質(zhì)量的虹膜圖像干擾、虹膜定位不精確和虹膜特征選取不當(dāng)?shù)纫蛩囟紩?huì)導(dǎo)致提取的虹膜特征穩(wěn)定性較差,從而降低整個(gè)識(shí)別系統(tǒng)的性能。所以對(duì)影響虹膜特征穩(wěn)定性的關(guān)鍵技術(shù)研究很有必要。本文首先梳理和分析了國內(nèi)外虹膜識(shí)別技術(shù)的研究現(xiàn)狀,對(duì)當(dāng)前虹膜識(shí)別中的幾個(gè)主要的虹膜識(shí)別算法進(jìn)行了分析研究,并將這些相關(guān)算法進(jìn)行了比較;然后從整體上詳細(xì)的介紹了虹膜識(shí)別系統(tǒng)的各個(gè)部分的內(nèi)容,以及采用的算法技術(shù);最后詳細(xì)的介紹了本文在虹膜識(shí)別的關(guān)鍵技術(shù)上的創(chuàng)新和改進(jìn),并在中科院CASIA_V1.0數(shù)據(jù)庫和實(shí)驗(yàn)室自建數(shù)據(jù)庫BA上對(duì)改進(jìn)的算法進(jìn)行了實(shí)驗(yàn)分析。本文的主要研究內(nèi)容如下:1.為了消除低質(zhì)量的虹膜圖像(采集設(shè)備和采集環(huán)境的差異)對(duì)識(shí)別系統(tǒng)性能的影響,本文采用了基于Fourier變換的虹膜圖像質(zhì)量評(píng)價(jià)算法,去除采集的低質(zhì)量圖像,降低虹膜識(shí)別系統(tǒng)的誤識(shí)率。2.針對(duì)虹膜外圓定位時(shí)受圖像質(zhì)量影響較大,搜索范圍增大耗時(shí)較長的問題,研究了一種結(jié)合統(tǒng)計(jì)知識(shí)和微分積分定位的虹膜外圓定位算法,縮小了圓周的定位精度,提高了定位速度。3.仔細(xì)的研究了虹膜紋理的局部細(xì)節(jié)特征,提出了一種利用多通道的二維Gabor濾波器對(duì)虹膜子塊局部細(xì)節(jié)進(jìn)行量化的特征提取方法,并結(jié)合相位信息組合成特征向量,以此來編碼虹膜特征。對(duì)數(shù)據(jù)庫中的圖像樣本進(jìn)行實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果表明,本文采用的基于Fourier變換的虹膜圖像質(zhì)量評(píng)價(jià)算法、改進(jìn)的虹膜外圓定位算法和基于關(guān)鍵點(diǎn)間特征向量的虹膜特征提取算法,使得提取的虹膜特征具有較高的穩(wěn)定性,并提高了識(shí)別系統(tǒng)的速率和識(shí)別正確率,符合現(xiàn)有虹膜識(shí)別系統(tǒng)開發(fā)技術(shù)要求。
[Abstract]:With the further development of information technology in China, information security has become an important issue of social concern. Biometric recognition technology has been widely paid attention to and applied because of its own important characteristics, among which iris recognition technology is highly accurate, unique and stable. It is considered to be a biometric technology with high research value and application prospect. However, in practical application, there are still many defects in iris recognition technology, such as low quality iris image interference, inaccurate iris location and improper selection of iris features, which will lead to poor stability of extracted iris features. Thus, the performance of the whole recognition system is reduced. Therefore, it is necessary to study the key techniques that affect the stability of iris features. In this paper, firstly, the research status of iris recognition technology at home and abroad is analyzed and analyzed, and several main iris recognition algorithms are analyzed and compared. Then the content of each part of iris recognition system is introduced in detail, and the arithmetic technology is introduced in detail. Finally, the innovation and improvement of the key technology of iris recognition in this paper are introduced in detail. The improved algorithm is analyzed experimentally on CASIA V1.0 database and lab database BA. The main contents of this paper are as follows: 1. In order to eliminate the influence of the low quality iris image (the difference between the acquisition equipment and the acquisition environment) on the performance of the recognition system, an iris image quality evaluation algorithm based on Fourier transform is adopted in this paper to remove the collected low quality image. Reduce the error rate of iris recognition system. 2. Aiming at the problem that the iris outer circle location is greatly affected by image quality and the search scope is increased, a new iris circle location algorithm combining statistical knowledge and differential integral positioning is studied, which reduces the accuracy of the circle location. Improved positioning speed. 3. In this paper, the local details of iris texture are studied carefully, and a feature extraction method based on multi-channel two-dimensional Gabor filter is proposed to quantize the local details of iris sub-block, and the feature vector is formed by combining the phase information. This is used to encode iris features. The experimental results on the image samples in the database show that the iris image quality evaluation algorithm based on Fourier transform, the improved iris outer circle location algorithm and the iris feature extraction algorithm based on the feature vectors between key points are adopted in this paper. The extracted iris features are of high stability, and the rate and accuracy of the recognition system are improved, which meets the technical requirements of the existing iris recognition system.
【學(xué)位授予單位】：河南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP309

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 裴成龍;楊亮;付倜儻;;一種基于OV7725的低光照虹膜采集裝置[J];儀器儀表用戶;2015年04期

2 張震;張英杰;;基于支持向量機(jī)與Hamming距離的虹膜識(shí)別方法[J];鄭州大學(xué)學(xué)報(bào)(工學(xué)版);2015年03期

3 陳書貞;于倩;練秋生;;聯(lián)合多尺度分塊和協(xié)作表示的虹膜識(shí)別算法[J];信號(hào)處理;2014年09期

4 李星光;孫哲南;譚鐵牛;;虹膜圖像質(zhì)量評(píng)價(jià)綜述[J];中國圖象圖形學(xué)報(bào);2014年06期

5 苑瑋琦;劉笑楠;孫曉;滕海;;一種虹膜圖像塊狀紋理檢測算法[J];儀器儀表學(xué)報(bào);2014年05期

6 李歡利;郭立紅;王心醉;李小明;董月芳;方艷超;;基于加權(quán)Gabor濾波器的虹膜識(shí)別[J];吉林大學(xué)學(xué)報(bào)(工學(xué)版);2014年01期

7 陳傳虎;鄒德旋;劉海寬;;應(yīng)用統(tǒng)計(jì)距離實(shí)現(xiàn)虹膜定位[J];光學(xué)精密工程;2012年11期

8 糜蘇，

本文編號(hào)：2043136