本文關(guān)鍵詞：手指生物特征變換與超球�；椒ㄑ芯�　出處：《中國民航大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 多模態(tài)生物特征 特征變換 鄰域特征矩陣 超球粒融合

【摘要】：傳統(tǒng)的單模態(tài)生物特征識(shí)別穩(wěn)定性差,不能滿足人們的實(shí)際需求。為了提高生物特征識(shí)別系統(tǒng)的有效性和可靠性,近幾年,利用多模態(tài)特征進(jìn)行人的身份識(shí)別逐漸成為了研究熱點(diǎn)。然而,多模態(tài)特征融合識(shí)別算法在特征融合時(shí)存在著很多亟待解決的問題,例如融合時(shí)多模態(tài)特征圖像尺寸不一,以及如何選取更有效的融合方式等。本文以指紋、指靜脈和指節(jié)紋為研究對(duì)象,嘗試通過特征變換和超球�；姆绞浇鉀Q多模態(tài)特征識(shí)別現(xiàn)存的一些問題。本文的主要工作如下:(1)針對(duì)多模態(tài)特征的尺度差異性問題設(shè)計(jì)了兩種特征變換的方法。1)在空域上,通過均勻劃分和超像素劃分兩種思路,將不同模態(tài)的圖像化為相同的塊數(shù),并在每個(gè)圖像塊內(nèi)提取相同維度的特征;2)提出了鄰域特征矩陣生成法,依據(jù)圖像的Gabor方向特征進(jìn)行特征變換,實(shí)現(xiàn)了將三模態(tài)不同維度的特征化為相同維度特征的目的,同時(shí)也對(duì)數(shù)據(jù)進(jìn)行了有效降維,減少了系統(tǒng)的運(yùn)算代價(jià)。(2)針對(duì)多模態(tài)特征的融合問題構(gòu)建了一個(gè)超球粒聚類的融合模型。利用超球粒之間的合并算子和給定閾值將同一個(gè)體的不同模態(tài)特征融合成一個(gè)超球粒,作為后續(xù)識(shí)別的依據(jù)。同時(shí),采用超球粒的三角形融合模型,進(jìn)一步驗(yàn)證了利用超球粒的思想解決三模態(tài)特征融合識(shí)別問題的可行性。本文通過大量實(shí)驗(yàn)驗(yàn)證了提出的方法,實(shí)驗(yàn)結(jié)果表明,利用提出的鄰域特征矩陣生成法,結(jié)合超球粒聚類融合模型,較傳統(tǒng)的生物特征識(shí)別方法可以達(dá)到更高的識(shí)別精度。
[Abstract]:Single modal biometric stability of the traditional difference, can not meet the actual needs of the people. In order to improve the effectiveness of biometric identification systems and reliability, in recent years, the use of multimodal features for human identification has become a hot topic. However, multi-modal feature fusion recognition algorithm has some problems with in feature fusion, such as fusion of multimodal feature image sizes, and how to select more effective fusion methods. Based on fingerprint, finger vein and knuckleprint as the research object, attempts to change the characteristics of the chondrules and super multi-modal feature recognition of some existing problems. The main work of this paper are as follows: (1) in order to solve the problem of the scale difference of multi modal features designed two methods of feature transform.1) in space, through the uniform partition and super pixels divided two kinds of ideas, will The image of different modes for the same number of blocks, and the same dimension feature extraction in each image block; 2) proposed the neighborhood feature matrix generation method based on Gabor transform, the feature directions of the image feature, realize the purpose of the three mode characteristics of different dimensions into the same dimensions, but also effectively to reduce the dimensionality of the data, the system to reduce the cost of computation. (2) for the fusion of multi modal features constructed a fusion clustering model. Using the super chondritic merge operator and the given threshold will be different between super chondritic modal characteristics of the same individual into a super chondrules, as subsequent recognition basis. At the same time, the spherical triangle fusion model is further verified by super chondritic thought to solve the feasibility of three modal feature fusion recognition problem. The proposed method was verified by experiments, The experimental results show that the proposed neighborhood feature matrix generation method and the hyper sphere clustering fusion model can achieve higher recognition accuracy than the traditional biometrics method.

【學(xué)位授予單位】：中國民航大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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