classified image 中文意思是什麼

classified image 解釋
分類圖像
  • classified : adj. 1. 分類[分級]的。2. 機密的，保密的。
  • image : n 1 像，肖像，畫像；偶像。2 影像，圖像。3 相像的人（或物）；翻版。4 形像，典型。5 形像化的描繪。6...
  1. Three commixed still image coding algorithms are proposed based on them and such ideas as : zerotree coding, wmse ( which is based on mankind visual characteristics ), classified vector quantization with different vector structures and classification methods. the chapter gives the principium analysis, realization schemes and simulation results of the proposed algorithms

    在此基礎上，結合零樹編碼思想，以及基於人眼視覺特性和分類矢量量化的思想，根據不同的矢量構成和分類方法提出了三種混合型靜止圖像編碼方法，給出了演算法原理的分析、實現方案和模擬結果，最後對本章方法作出分析總結。
  2. This paper studies using the k - means clustering algorithm to classified the obtained image, submits through two phases to retrieve the image and adjusts the weight using the relevant feedback method

    本文研究利用k均值聚類方法對檢索得到的圖像進行分類，通過兩階段提交對圖像進行篩選，並利用相關反饋方法來調整權重。
  3. ( 4 ) to record the running situation. and this software was developed by c + + under microsoft vc + + 6. 0 and is composed of 5 modules : the initial module to finish the video card and i / o card initializations ; the start - stop module to create and destroy the thread used to supervise light room and process image ; the image - capturing module to capture the image from ccd to ram ; the image processing module to get classified information through analysis ; the signal i / o module to send the signals to the outside and also to send outer information to the inside ; the system log module to record the running situation of the system and the quantity of detected eggs

    系統由5個模塊組成：初始化模塊完成圖像採集卡和數字量i o卡的初始化；啟動停止模塊建立和消亡用於監控光室狀況和進行圖像處理與分析的線程；圖像採集模塊將光室中所成的像通過ccd經由圖像採集卡採集到主機內存中；圖像處理模塊對主機內存2001碩士論文摘要中的圖像進行分析，得出所需要的分級信息;信號1 / 0模塊將得出的分級信號送出至計算機外部，同時也將計算機外部的控制反饋信息傳至計算機內部;系統日誌模塊記錄系統的啟動運行情況和當前系統檢測鴨蛋的數量。
  4. Fingerprint image is classified into predefined categories. it can greatly reduce matching time because the matching is implemented in a sub - category

    指紋圖象被劃分到預先設定的某個類別，這樣匹配工作就可在一個子類中進行，從而大大節省運算和匹配時間。
  5. At present the fractal based applications in image domain are approximately classified into two categories : according to the characteristic of self - similar of fractal, people imitate and compress the natural image using mapping transformation method. this is one category. the other is according to the features of fractal and fractal dimension, people set up image models, investigate the main geometric features of the images and process them effectively

    目前分形在圖像中的應用大致可以概括為兩類：一類是利用分形的自相似特性，採用映射變換的方法對自然界景物進行模擬，對圖像進行壓縮編碼；另一類是根據分形及分數維的特徵參量來建立模型，通過對模型參數的研究，有效地進行圖像分析和處理。
  6. After eroding the image is classified and the initial marker result is obtained

    分類粘連圖像、獲取圖像的初始標記。
  7. The image segmentation is done with the approach of region growing based on block mean and variance. considering the size of extracted objects and their relative position information, get rid of the " noise " objects and merge the meaningful fragmentary regions into their corresponding bigger ones. finally all pixels in non - object blocks are classified into their corresponding adjacent objects

    圖像首先被分成合適大小的子塊，子塊的色彩均值和方差值作為像素群的屬性，用基於子塊的區域生長來進行圖像分割；根據提取出的對象大小以及它們的空間位置關系，去除掉過小的噪聲對象同時將有意義的小對象合併到其所屬的大對象中；最後處于邊界的子塊將逐像素地歸類到對應的相鄰對象中。
  8. According to the relevant materials of field investigating and existing land desertization, various image characteristics of different desertization degrees were summed up. this study has realized translating by hand to the desertification land supported by expert system on the basis of the categorised system after choosing the classified training areas and adopting the translated method through the eyes

    本研究根據野外調查和現有的土地沙漠化的有關資料，分析總結了不同沙漠化程度的影像特徵；並根據所得到的分類系統，選取分類的訓練區，採用目視解譯的辦法，實現了對沙漠化土地的在專家系統支持下的人工解譯。
  9. The main contents of this thesis are summarized as follow : ( 1 ) the course of the data mining development is reviewed and the role which the data mining played in kdd is definite. the components has been classified according to the task of the data mining, and in each component the technic has been summarized. the model which apply to image data mining is proposed based on these components

    本文的主要研究工作有以下幾個方面： 1 、回顧了數據挖掘的發展過程，明確了數據挖掘在知識發現中的地位，將數據挖掘按照挖掘任務劃分為幾個模塊，並對每個模塊中挖掘技術進行總結，提出了一個適合圖象數據挖掘的模型。
  10. Using the different gradients of the plate area and the non - plate areas in a car image, a neural network is trained. then the image is classified with the trained network. finally, with the help of the projection features and the geometric features of car license plate, the license plate is located

    該演算法利用牌照區和非牌照區不同的梯度特徵對神經網路進行訓練，之後用訓練好的神經網路對圖像進行分類，最後結合牌照的投影特徵和幾何特徵實現牌照的定位。
  11. To effectively extract edges, edge pixels are classified according to the difference of intensity distribution, and multiple effective edge features are defined. edges are detected by applying fuzzy reasoning ( min - max centroid method ), based on local image edge characteristics

    該方法在重新定義邊緣特徵的基礎上，引入模糊推理理論，從而形成了基於多邊緣特徵和模糊推理的邊緣檢測方法。
  12. A classified vector quantization scheme of still image based on wavelet transform

    一種基於小波分解的圖象分層分類矢量量化方法
  13. Envi, a software that can deal with remote sensing image, was used to process tm image. according to the investigation on the spot, the grassland taxonomy of our country and the criterion of estimating environment quality, the vegetative cover in the source area of the yellow river was classified as five kind in this thesis

    本文利用envi遙感圖像處理軟體加工處理的tm衛星影像，根據實地調查，按全國草地調查統一分類法，結合生態環境質量評價標準，本文將黃河源區植被覆蓋劃分為5個等級，並採用非監督分類法對黃河源區tm影像進行分類。
  14. This chapter first introduces the principium of trellis coded vector quantization, then focuses on analyzing the algorithm of wavelet image classified weighted tcvq and its realization process, also gives tcvq application to wavelet image coding and its simulation results

    首先分析了網格編碼矢量量化的原理，在第三章矢量量化的基礎上詳細介紹了小波圖像分類加權tcvq演算法的原理和實現過程，並給出了tcvq在小波圖像量化中的應用實例和模擬結果。
  15. We attempt to exploit various machine - learning techniques to learn the heuristic knowledge from users " experiences, so that the image segmentation system can have some human ability in adaptively selecting optimal algorithm and corresponding parameters. learning based image segmentation system can be classified i

    希望使用機器學習的技術，通過從用戶對訓練圖像集的分割和評價中學習相應的啟發式知識，以此使系統能夠根據圖像的特徵，為不同的圖像靈活的選擇參數或演算法，從而自動實現令人滿意的分割。
  16. In the research, the system captures real - time images based on the sdk, and saves the image data into buffers which are created by the system. the important and primary parts are got using the programs which are designed to process and analyze the image data in the buffers, and the geometrical features such as area, perimeter, moment invariants and fourier descriptor, are measured. the parts are classified according to the threshold of each geometrical feature with the image database

    課題研究中，在設計的試驗平臺上，通過攝像頭和sdk開發包對零件進行實時圖像採集，並將其存入開辟的數據緩沖區內;由設計的圖形處理模塊對緩沖區內的數據採用各種演算法進行分析處理，形成研究中感興趣的重要圖像;調用圖像識別判斷模塊，主要提取了零件的周長，面積，慣性矩，傅立葉描繪子等形狀特徵參數，根據定義的識別函數，並結合圖像數據庫，進行零件識別或缺陷檢測。
  17. According to the style of image decomposition, sbnc maybe classified into two kinds : sliced orthogonal nonlinear generalized correlation ( song correlation ) based on sliced orthogonal nonlinear generalized decompositionand morphological correlation ( mc ) based on threshold decomposition. comparedwith common linear correlation ( lc ), the output performances of sbnc are far bet - ter in either discrimination or noisy robustness

    根據圖像分解方式的不同， snbc分為兩類:基於片狀正交非線性廣義分解的片狀正交非線性廣義相關器（ slicedorthogonalnonlineargeneralizedcorrelation ，簡稱song相關器）和基於閾值分解的形態相關器（ morphologicalcorrelation ，簡稱mc ） 。
  18. The paper analyzes binary - split gradient & threshold initial codebook generation - algorithms, codebook generation algorithms based on kohonen self - organizing feature map neural network, a fast codeword searching algorithm using l2 - norm pyramid data structure, side - match vector quantization algorithms, and a fuzzy classified vector quantization algorithm, systematicly explores their application to image compression, computer simulation results show that they are practical and efficient

    文中重點分析了二元分裂梯度與閾值初始碼書生成演算法、基於kohonen自組織特徵映射神經網路的碼書生成演算法、基於l2范數金字塔數據結構的快速碼字搜索演算法、邊緣匹配矢量量化演算法、模糊分類矢量量化演算法，系統地研究了它們在圖像壓縮編碼中的應用，並進行了計算機模擬，實驗結果表明這些演算法是實際有效的。
  19. The research work of this paper can be classified in the following respects : 1 in the aspect of moment techniques and properties, we mainly discuss the definition and properties of regular moment, orthogonal moments and other moments and invariants. we also compare and evaluate the performance of various moments in image representation, noise sensitivity, and information redundancy

    本文在前人研究的基礎上，從以下幾個方面進行研究和創新： 1 、在矩技術及其特性方面，著重探討了規則矩、正交矩以及其它常用矩及不變量的定義和性質，並就各種矩在圖像表示能力、噪聲敏感度和信息冗餘等方面的性能進行了比較與分析。
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