palmprint 中文意思是什麼

palmprint 解釋
掌紋。

  1. 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

    掌紋由於易於獲取，主特徵明顯、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。
  2. Looking down simba sees that his forepaw fits inside just the palmprint of his father ' s paw

    （辛巴向下看的時候發現它的整隻前腳才只有他父親的腳掌心那麼大。 ）
  3. Palmprint recognition based on fourier transform

    基於傅立葉變換的掌紋識別方法英文
  4. Palmprint feature extraction based on wavelet transform

    基於小波變換的掌紋特徵提取
  5. Wavelet based independent component analysis for palmprint identification

    基於小波分解的獨立分量掌紋識別方法
  6. A novel palmprint image denoising algorithm based onwavelet transform

    一種新的基於小波變換的掌紋圖像去噪演算法
  7. Wavelet energy feature extraction and matching for palmprint recognition

    用於掌紋識別的小波能量特徵的提取和匹配
  8. Research and design of online identification authentication with palmprint

    基於在線掌紋的身份驗證系統的研究與設計
  9. Each kind of palmprint pattern is described by parameters in wavelet domain that learned form samples by estimation

    通過樣本學習，利用參數佑計的方法，每種掌紋模式的理想模型表示為小波域內的特定參變量。
  10. 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徵識別技術之一，掌紋識別方法的開發具有重要的現實意義。
  11. 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徵提取演算法的思想、作用和實現過程。
  12. 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

    採用基於掌紋圖像灰度特性的方法提取出掌紋的主線特徵，以極坐標的形式定義在線掌紋的特徵空間並降維處理，最後用神經網路作為匹配演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。
  13. 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徵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採集設備的價格比虹膜採集設備的價格要低廉得多掌紋特徵比簽名特徵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徵包括主線和皺褶，這些線特徵具有很強的區分能力，並可以在低解析度圖像中提取出來可以將手掌上的各種特徵融合在一起建立一個高精度的生物識別系統等。
  14. 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並廣泛應用的行為特徵;手寫簽名的採集設備價格比虹膜和掌紋等採集設備更低廉;作為一種行為特徵，手寫簽名比人體物理特徵更難于模仿等。
  15. 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

    該演算法從掌紋樣本中學習不同類別的理想模板，並將理想模板的參數作為特徵用於模式分類，由於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徵提取的貢獻，因此達到非常好的識別效果。
  16. 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採集現狀，目前各種採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、高解析度的、基於多方向光源圖像融合的掌紋採集系統，滿足了掌紋診病後期診斷對高質量圖像的要求。
  17. 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，用於掌紋特徵提取，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徵間的本質結構。
  18. 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

    論文把兩種特徵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神經網路分類器、線性神經網路與最小分類器、線性神經網路與bp神經網路分類器四種組合，最後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。
  19. 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，通過大量的樣本採集融合實驗，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。
  20. 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

    對于採集模塊的實現，首先詳細分析了手掌及掌紋的特點，並針對這些特點，設計了一種雙方向照明、高解析度的採集設備，經大量樣本採集實驗表明，該設備能夠將手掌上諸多尺度的細節特徵很好的保存下來，達到較高的空間解析度。
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