本文關(guān)鍵詞： 掌紋識別 特征提取 LBP 相位特征 Gabor濾波器 非高斯Gabor濾波器　出處：《昆明理工大學》2017年碩士論文　論文類型：學位論文

【摘要】：近年來,隨著生物識別技術(shù)的廣泛發(fā)展,相關(guān)的研究人員對此表現(xiàn)出極大的關(guān)注度,是近年來研究的熱點之一。生物識別技術(shù)有其自身的特點,穩(wěn)定性高、安全并且方便,從而得到了快速的發(fā)展。掌紋是用來描述手掌內(nèi)部表面上所有紋線的統(tǒng)稱,它包括主線、皺褶和乳突紋等。與其他生物特征識別方法相比,掌紋特征信息更加豐富、圖像采集簡便、使用的用途廣泛,受眾接受度高,能夠有效的識別,所以掌紋識別用來作為一種身份識別方法,得到了普遍性的認可。掌紋識別經(jīng)過十多年的研究,在理論和實踐方面都有了一定的基礎。在掌紋圖像的預處理方面趨于成熟。由于掌紋表面紋線深淺不一、方向呈現(xiàn)無規(guī)律變化,并且導致掌紋圖像變化及變形的因數(shù)較多,對最終的識別率造成了嚴重的干擾。本文研究當下一些主流的掌紋識別算法,從掌紋的特征紋理分析、特征融合方向提出精確度高、識別效果好的識別算法,本文的研究如下:1、對文中涉及的掌紋識別預處理算法進行研究分析,提取到掌紋圖像的感興趣區(qū)域(ROI);2、提出一種基于非高斯Gabor·濾波器的掌紋識別算法。我們構(gòu)建出了非高斯Gabor濾波器的函數(shù),對經(jīng)過預處理的掌紋圖像做非高斯Gabor濾波處理,再計算濾波后圖像的相位信息,得到相位矩陣。將此相位矩陣進行分塊處理,經(jīng)過相位編碼規(guī)則計算其相位特征,同時提取到各分塊的LBP特征,最后連接各分塊的特征向量組成了原始圖像的特征向量,最后把該向量送入分類器中進行分類識別;3、在Polyu_Pamprint_Database掌紋庫上進行仿真實驗,并跟與Gabor濾波器的掌紋算法對比實驗,從實驗結(jié)果上,本文提出的算法更具有高效性,有良好的識別精度。
[Abstract]:In recent years, with the extensive development of biometrics technology, the researchers concerned have shown great attention to it, which is one of the hot research topics in recent years. Biometric recognition technology has its own characteristics and high stability. Palmprint is a general term used to describe all the lines on the inner surface of the palm. It includes the main line, wrinkle and mastoid stripe, etc. Compared with other biometric methods, palmprint is used to describe all the lines on the inner surface of the palm. Palmprint feature information is more abundant, image collection is simple, the use of a wide range of applications, high audience acceptance, can be effectively recognized, so palmprint recognition is used as an identification method. After more than ten years of research, palmprint recognition has a certain theoretical and practical basis. In the palmprint image preprocessing tends to mature. Due to the depth of the palmprint surface lines are different. The direction of the palmprint image changes irregularly, and leads to more factors of palmprint image change and deformation, resulting in serious interference to the final recognition rate. This paper studies some current mainstream palmprint recognition algorithms. From the palmprint feature texture analysis, feature fusion direction proposed a high accuracy, recognition effect of the recognition algorithm, this paper research as follows: 1, the palmprint recognition pre-processing algorithm involved in this paper research and analysis. The region of interest is extracted from palmprint image. 2. A palmprint recognition algorithm based on non-#china_person0# Gabor 路filter is proposed. The function of non-#china_person1# Gabor filter is constructed. The pre-processed palmprint image is processed by non-#china_person0# Gabor filter, then the phase information of the filtered image is calculated, and the phase matrix is obtained. The phase matrix is processed in blocks. The phase features are calculated by the phase coding rules, and the LBP features of each block are extracted at the same time. Finally, the feature vectors connected to each block constitute the feature vectors of the original image. Finally, the vector is sent into the classifier for classification and recognition. 3. The simulation experiment is carried out on Polyu_Pamprint_Database palmprint database and compared with the palmprint algorithm of Gabor filter. The algorithm proposed in this paper is more efficient and has good recognition accuracy.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41

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本文編號：1473516