P - palmprint 中文

palmprint 掌紋。

palmtop
According to the fact that the basic features of apalmprint , including principal lines , wrinkles and ridges , havedifferent resolutions , in this paper we analyze palmprints using amulti - resolution method and define a novel palmprint feature , whichcalled wavelet energy feature , based on the wavelet transform . wef can reflect the wavelet energy distribution of the principal lines , wrinkles and ridges in different directions at different resolutions scales , thus it can efficiently characterize palmprints . this paperalso analyses the discriminabilities of each level wef and , according to these discriminabilities , chooses a suitable weight for each levelto compute the weighted city block distance for recognition . theexperimental results show that the order of the discriminabilities ofeach level wef , from strong to weak , is the 4th , 3rd , 5th , 2nd and 1stlevel 作為對現有人體生物特征識別技術的重要補充，掌紋識別有著其獨特的優點：掌紋比指紋含有更多的可區分信息掌紋采集設備的價格比虹膜采集設備的價格要低廉得多掌紋特征比簽名特征更為穩定掌紋識別可獲得比人臉識別更高的識別精度掌紋含有獨特的線特征包括主線和皺褶，這些線特征具有很強的區分能力，并可以在低分辨率圖像中提取出來可以將手掌上的各種特征融合在一起建立一個高精度的生物識別系統等。
Finally , combining the two extraction methods with the two classification methods , the thesis put forward four models of palmprint recognition : k - l + ld model , k - l + nn model , nn + ld model and nn + nn model . the experiments show the accuracy , efficiency and the fault tolerance ability of these models . in terms of their characteristic , we can apply them in various fields 論文把兩種特征提取方法和兩種分類器設計方法進行結合，提出k - l變換與最小分類器、 k - l變換與bp神經網絡分類器、線性神經網絡與最小分類器、線性神經網絡與bp神經網絡分類器四種組合，最后對四種識別方法進行比較，根據它們識別的準確率、效率以及容錯能力對識別結果進行分析，總結出各種方法的優缺點，根據它們的特點，提出在不同方面的應用。
Through a lot of merging experiments on the samples , this paper devise a fusion way based on the features of the palm and the palmprint , which is suitable to preserve the multi - scale palmprint features . the merging module finally provides the detailed images that merged form different lighting images for the later modules in palmprint diagnosis , makes it possible to obtain the information that deeply hidden in the complex lines of the palm 圖像融合模塊則是系統工作的中心,通過大量的樣本采集融合實驗,本文得出一種依據掌紋特點、最適合保存包含多尺度細節紋理的掌紋圖像的融合方法,它為后續掌紋診病處理提供了融合后的、包含有大量信息的掌紋圖像,實現了多方向細節觀察的目的。
Handwritten signature has its own virtues : handwritten signature has been a human behavior characteristic and been widely accepted and applied since ancient times ; online signature capture devices are much cheaper than iris and palmprint devices ; handwritten signature is more difficult imitated than other personal physical characteristics . therefore , online handwritten signature verification is hotspot in the biometrics field 簽名鑒別具有其獨特的優點:手寫簽名自古以來就是一種被人們普遍認可并廣泛應用的行為特征;手寫簽名的采集設備價格比虹膜和掌紋等采集設備更低廉;作為一種行為特征,手寫簽名比人體物理特征更難于模仿等。
In this paper , two novel palmprint recognition methods are proposed in order to overcome the drawback of current algorithms . the whole design and implementation of palmprint recognition system including image acquisition , preprocessing , the basic idea and implementation of palmprint feature extraction and automatic palmprint classification and test are given 為了克服現有算法的不足,本文提出兩種新的掌紋識別算法,并給出掌紋識別系統的總體設計和實現過程,包括圖像獲取和預處理,掌紋特征提取方法的基本思想和實現,以及掌紋的自動分類和測試。
For the implement of the capturing device module , we first discuss the features of the palm and the palmprint , through which we design a device that has two - direction lighting , and has a very high resolution . through mass experiments on the capturing , the device does have the ability to preserve the details in the palms 對于采集模塊的實現,首先詳細分析了手掌及掌紋的特點,并針對這些特點,設計了一種雙方向照明、高分辨率的采集設備,經大量樣本采集實驗表明,該設備能夠將手掌上諸多尺度的細節特征很好的保存下來,達到較高的空間分辨率。
First in this paper we analyze the current situation in samples capturing of palmprint diagnosis , as the existed systems have lots of disadvantages , the demands of sampling capture cannot be fulfilled , we design a capturing system which has a relative high precise rate , and high resolution , and is based on multi - lighting images fusion , and really be able to provide excellent palmprint samples for the later process of palmprint diagnosis 本文首先分析了目前掌紋診病圖像樣本的采集現狀,目前各種采集系統存在諸多難以克服的缺陷,無法滿足現階段掌紋診病對于掌紋圖像樣本要求,因此設計了一套高精度、高分辨率的、基于多方向光源圖像融合的掌紋采集系統,滿足了掌紋診病后期診斷對高質量圖像的要求。
The paper abstracts out the palmprint mainline characteristic owing to palmprint image gradation by the gray value characteristic property method , defining the online palmprint characteristic space with the form of the polar coordinate and compressing the dimension , at last we use the neural network to accomplish the design of identification authentication system with the on - line palmprint as the mating algorithm . based on this , a fast and reliable system of identification authentication can be built 采用基于掌紋圖像灰度特性的方法提取出掌紋的主線特征,以極坐標的形式定義在線掌紋的特征空間并降維處理,最后用神經網絡作為匹配算法完成在線掌紋身份驗證系統的設計,以此為基礎建立了快速、可靠的新型身份認證系統。
Up to now , many traits in human body have been applied , such as fingerprint , palmprint , iris , face , hand shape and signature , etc . in the thesis , we propose a novel personal identification technology base on hand back and develop a prototype of hand back based identification in this paper 截至目前,已經用于身份識別的人體生物特征包括指紋、掌紋、虹膜、人臉、手形、簽名等。在本論文中,研究了一種新的生物特征識別技術? ?手背識別技術,并實現了手背識別系統原型。
Many common biometric features , such as fingerprint , face , iris , palmprint , voice , signature etc . , have the properties that they are possessed by everyone , are different with different person and keep stable in a long period . they cannot be stolen nor lost , fake and are difficult to be forged or imitated . therefore , they are very suitable for the personal authentication 常見的人體生物特征包括:指紋、人臉、虹膜、掌紋、語音、簽名等,這些人體生物特征通常具有“人人擁有、人人不同、長期不變”的特點,并且不易遺忘和丟失,也難以偽造和模仿,所以很適合用來進行身份識別或鑒別。
In order to deal with the unknown transformations of samples as a result of preprocessing and improve the system recognition performance further , a palmprint feature extraction method based on template learning in wavelet domain is designed and proposed . this algorithm learns the ideal templates of different classes from palmprint samples , whose parameters are regarded as 該算法從掌紋樣本中學習不同類別的理想模板,并將理想模板的參數作為特征用于模式分類,由于考慮了子圖樣本內在存在的平移和旋轉變換,不同類型小波系數對特征提取的貢獻,因此達到非常好的識別效果。
As palmprint is typical of ease acquisition , and its major feature is apparent , stability and divisibility , palmprint automatic identification is a very potential identification technology . however , the research and application of biological feature identification based on palmprint are very few due to the complexity , diversity and variableness of palmprint 掌紋由于易于獲取，主特征明顯、穩定、具有可分性等特點，以及掌紋自動識別系統具有直接、友好、方便、良好的唯一性和應用范圍廣的優點，因此是一種很有發展潛力的身份識別方法。
According to the speciality of palmprint , this paper proposes a recognition method based on algebraic feature . in order to extract the global feature of palmprint by pca ( principal component analysis ) , k - l transform and nn ( linear neural network ) method is presented 本文根據掌紋本身的特點，結合所處理的掌紋圖像的特點，提出有針對性的pca ( principalcomponentanalysis )特征提取方法，分別應用了k - l變換方法，線性神經網絡方法對掌紋的全局特征進行提取。
Independent component analysis has particular advantages in image processing . used for palmprint feature extraction , it can ensure the components to be irrelevant and statistical independent among each other , and can more roundly describe the essent . . 獨立分量分析方法在圖像處理中具有獨特的優勢，用于掌紋特征提取，使得變換后的各分量之間不僅互不相關，而且還盡可能的統計獨立，能更全面的揭示掌紋特征間的本質結構。
In this paper , two kinds of feature extraction methods are proposed based on former work of palmprint recognition and the characteristics of inner palm ; the design and implementation of these two algorithms as well as the test of performance are given 本文在分析現有掌紋識別方法的基礎上,結合手掌內表面的特點提出了兩種新的掌紋特征提取方法,并分別給出了兩種識別算法的設計與實現過程,以及性能測試。
After the discussion of the line based and texture energy based palmprint recognition in detail , we analyze the advantages and disadvantages of these two algorithms and suggest an efficient combination of these two ways - - - two - level palmprint recognition 在詳細闡述了基于線特征和基于紋理能量的掌紋識別方法之后,我們分析了這兩種算法的優缺點,并給出了兩種方法的有效結合- - -兩層的掌紋識別方法。
The current popular technique in palmprint recognition - - - print feature based palmprint recognition technique is introduced via a review of palmprint recognition research history 通過對掌紋識別技術研究史的回顧,本文介紹了掌紋識別方面的主流技術- - -基于紋線特征的掌紋識別技術。
As the crucial part of palmprint recognition , this paper mainly focuses on the ideas and usefulness and implementation of these two feature extraction algorithms 作為掌紋識別的關鍵部分,本文著重闡述兩種特征提取算法的思想、作用和實現過程。
As one of the most important biometrics techniques , the development of palmprint recognition has a significant influence on real world 作為最重要的生物特征識別技術之一,掌紋識別方法的開發具有重要的現實意義。

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palmprint

palmprint 掌紋。

palmtop

As the crucial part of palmprint recognition , this paper mainly focuses on the ideas and usefulness and implementation of these two feature extraction algorithms 作為掌紋識別的關鍵部分,本文著重闡述兩種特征提取算法的思想、作用和實現過程。

As one of the most important biometrics techniques , the development of palmprint recognition has a significant influence on real world 作為最重要的生物特征識別技術之一,掌紋識別方法的開發具有重要的現實意義。