最大圖像區域 的英文怎麼說

中文拼音 [zuìdàtúxiàngqūyù]
最大圖像區域 英文
maximum image area
  • 最 : 副詞（表示某種屬性超過所有同類的人或事物） most; best; worst; first; very; least; above all; -est
  • 圖 : Ⅰ名詞1 （繪畫表現出的形象; 圖畫） picture; chart; drawing; map 2 （計劃） plan; scheme; attempt 3...
  • 像 : Ⅰ名詞1 （比照人物製成的形象） likeness （of sb ）; portrait; picture 2 [物理學] image Ⅱ動詞1 （在...
  • 區 : 區名詞（姓氏） a surname
  • 域 : 名詞（在一定疆界內的地方; 疆域） land within certain boundaries; territory; region
  1. The computational results of the particle images are agreement with the simulated datain reasonable, the most absolute difference of the displacement is 0. 6671 pixel at the x abscissa and 0. 7928 pixel at y abscissa ; the computational results are equal to the data form the algorithm of particle brightness - distribution pattern tracking ( the conventional cross - correlation algorithm ) at voluminous points, their discrepancy is only one pixel at few points, mostly in boundary area

    西安理工大學碩士學位論文最後，在visualfortran環境下給出了這種演算法的具體實現，處理模擬粒子圖像的結果與模擬數據比較吻合，最大位移絕對誤差在x方向是0 . 6671像素，在y方向是0 . 7928像素;計算結果與示蹤粒子灰度分佈模板法（基本的互相關法）在絕大部分點是相同的，只在少數點相差一個像素，而且大多出現在邊界區域。
  2. The computer acquires the image of dial gauge by high precision ccd video, after that the computer will process the dial gauge image by some image - processing algorithms such as image segmentations, edge searching, area segmentations and locating the pointer by the " circle ". at last the computer will recognise the dial pointer position and work out the precision of dial gauge in accordance with nation criterion of dial gauge. this study presents several optimum algorithms to realize quick recognition of the pointer and calibration lines of detected dial and improve the accuracy and real time quality of detecting

    本系統由計算機控制步進電動機的運動，進而驅動指示表表針的運動，通過高精度ccd攝像機實時獲取表盤圖像數據，同時進行表盤圖像的相關處理，包括閾值分割、邊緣檢測、圖像銳化以及區域分割和定心圓檢測等，最終快速識別出表盤指針所處位置，最後根據國家指示表類檢定規程所制定的演算法檢定出指示表的各種精度，本系統所採用的圖像處理演算法運算量少，速度快，從而大大提高了系統的實時性。
  3. This paper illustrates detailedly the thin groupware auto - adaptive recognition system ; it also illlustrates the procession of capture image and take indispensable foreclose to wipe off noise in order to get boundary easilyer. the recognition system uses " hough " transform method to make the recognition area orientation, and according to the unstable environment such as lights which leads to the change of the image ' s brightness, thresholds picture using an iterative selection method and then growing process for cell image segmentation based on local color similarity and global shape criteria, adaptively gets the best threshold to divide the washer off the background. the recognition system uses the classifier based on minimal - error - ratio bayes method to make decision after getting image characteristic

    本文詳細介紹了薄形組合件自適應識別系統；闡明了圖像的分通道自動採集過程，以及對採集到的原始圖像所進行的預處理方法。通過採用哈夫變換去除偽邊緣點的方法，有效地解決了識別區域的定位問題。針對裝配零件（主要是墊片）薄、小導致圖像信息少、識別難度大，以及材質不一導致採集到的組合件圖像亮度波動等問題，提出了使用最佳閾值迭代法和使用種子填充的圖像串列分割技術，自適應地找出最佳閡值，使墊片和背景分離，從而提取墊片數目信息。
  4. Moving object detection adopts a method of dynamic difference background image, whose principle is to calculate difference picture among the current frames and background images and take the motion adjudging threshold which owns maximum information entropy to determine moving area ; and dynamically updates background by using kalman filter. thus, the system realizes the judgment of the moving area under the complicated changing background

    運動目標檢測採用動態差分背景圖像法，其原理是利用序列圖像中當前幀圖像減去背景圖像，並採用使信息熵最大化的運動判決門限判定運動區域;採用kalman濾波動態背景生成實現了背景的動態更新;從而實現了復雜變化背景下圖像運動區域的判決。
  5. In this paper, a series of images photographed by aircraft is processed, and finally merged into a whole without redundancy

    本論文通過對系列航空照片的處理，最終把它們合成為一幅無冗餘的大區域圖像。
  6. 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。
  7. A theory using image local maximum modules, got by wavelet transform, as image feature, is promoted and proved well. finally, using image mosaic technique based on multi - resolution analysis, redundancies between images are eliminated. the whole image produced at last is a much bigger one without seam and distortion

    提出了圖像邊緣局部最大模作為匹配特徵的理論，並取得很好的效果；最終通過多分辨分析圖像融合技術消除圖像間的冗餘，並把它們合成為一幅無接縫、無畸變的、大區域圖像。
  8. On the base of the analysis, we build up the vector fields of neighborhood variation ; put our emphasis on the description of the image edges and the domains of visual similar grey - level with the vector fields. after that, we find out the two methods used to detect the edges, the one with the biggest vector field, and the other with the perpendicular vector - pair of the biggest variation difference. the neighborhood size has got the great influence

    在此基礎上，提出了基於鄰域灰度變化矢量場的圖像分割思想;建立了圖像鄰域灰度變化矢量場，並重點分析了鄰域灰度變化矢量場與圖像視覺邊緣、區域等特徵之間的關系;建立了最大鄰域灰度變化矢量的邊緣檢測運算元模型，基於鄰域灰度變化矢量場最大正交差異對的邊緣檢測運算元及區域檢測運算元模型;分析了鄰域選擇對邊緣擴展、噪聲抑制的影響。
  9. Firstly, with the application of both morphologic translation and human body feather analysis on binary graph, the human body contours are extracted by exploited moving information, producing perfect human face region segments ; secondly, in order to form an accurate border, the author presents an improved statistical color model, which has removed redundancy successfully ; finally, a high compression rate is achieved by way of combining wavelet transform and different chain codes

    首先利用運動信息分割出人體輪廓，並綜合運用人體的特徵與形態數學的方法成功地分離出人臉大致區域；然後採用基於改進統計彩色信息模型方法，精確分割出人臉區域，去掉了不相關的冗餘信息；最後提出了利用圖像小波變換結合差分鏈碼技術描述了人臉對象，並實現了高效的視頻壓縮。
  10. Such integra ting feature vector is used for building k dim e nsion gaussian m odel, whose param e ters are estim ated by an expectation - m a xi m i zation ( em ) algorithm, and then the resulting block - cluster m e mberships provide a segm entation of th e im age. after segm ented, a m e thod of param e ter - trimm e d average for describing re gion is proposed, of which the param e ter is decided by area and position of region dire ctly. the sim ilarity m easure between two im ages is defined by integrating properties of all regions in the im age

    文中先將圖像分成4 4小塊，各塊的顏色、紋理、位置特徵構成8維的特徵空間；在該空間中對得到的8維特徵矢量建立一個k維高斯模型，應用期望最大em演算法估計模型參數，產生的塊特徵-聚類隸屬度函數實現對圖像的分割；為減小分割演算法不確定性對檢索效果的不良影響，對得到的區域採用參數均衡平均特徵表示，其中參數的確定直接與區域的面積、位置有關。
  11. According to the fact that iris images cannot be compared for their different resolutions, a new method for normalizing iris region into fixed resolution by using minimum inner boundary resolution and minimum radius difference of inner boundary and outer boundary is presented

    摘要針對虹膜區域圖像大小不同，難以實現虹膜的比較問題，提出了根據虹膜最小內邊界周長確定角度解析度和根據虹膜最小內、外邊界半徑差確定徑向解析度的方法，將不同分辨的虹膜圖像轉換為相同解析度的矩形區域。
  12. The three primary color channels of color image are separately captured to the image acquisition board by using special hardware and software technology, therefore, three lines of seeds are parallel captured. contrastive test is done to compare advantage and disadvantage of threshold chosen method, which can either be chosen from trying or iteration, and predefined threshold chosen is selected, which result in lessen processing time. region labeling using sequential algorithm and seed object recognition are studied, and then the center of a region is calculated

    包括：為了有效地去除大量冗餘圖像信息，減少計算機存儲量，而採用的逐場採集和隔幀存方法；為實現三行播種通道種子信息的并行採集，圖像三分量獨立採集的軟硬體技術方法；對比實驗了自定義閾值選取與基於迭代方式的最優閾值的優缺點，選用了自定義閾值進行圖像分割，縮短了圖像處理時間：研究了基於序貫演算法的種子區域標記技術與種子目標識別技術，並進行了質心參數計算。
  13. In order to further video analysis, an algorithm of abrupt shot boundary detection based on fuzzy clustering neural network ( fcnn ) is proposed, and it has the advantages of high precision as well as robust to fast move. caption segmentation is the key to the whole process, fcnn can also be utilized to locate caption region, however, the technique is time - consuming. thus an improved projection segmentation method is presented, and the experimental results show that it is simple and practical, and fits for real - time processing

    為了便於后續的視頻分析，提出了一種基於模糊聚類神經網路（ fcnn ）的鏡頭突變檢測演算法，實現視頻鏡頭分割，該演算法具有檢測精度高、對運動穩健等優點；區域定位是字幕提取的關鍵一環，同樣利用fcnn分類器可實現字幕定位，但其運算量大，定位精度不高，因此提出了一種改進的投影分割方法實現字幕區域定位分割，實驗表明其簡單實用，適于實時處理；考慮到單個字元背景相對簡單，為此提出了一種基於單字元的字幕二值化演算法，最終在經由字元分割、二值化及殘留背景像素清除之後，得到了清晰、高質的字幕圖像，字元識別結果證明了這一點。
  14. The calculation formula of micropiv technique is the original definition of velocity : v = [ s ( t2 ) - s ( tl ) ] / ( t2 - tl ). on the two neighboring frame of images, we search for the two small areas which have the largest correlation. by dividing their distance by their shooting interval, we got the average velocity of this small area in this interval, and then got the velocity of full flow

    Piv測試原理的計算公式，是速度的原始定義： v = [ s （ t _ 2 ） - s （ t _ 1 ） ] （ t _ 2 - t _ 1 ） 。在相鄰兩幀圖像上，找出相關度最大的兩個小區域，用它們之間的距離除以兩次拍攝之間的時間間隔，就得到這個小區域在間隔時間內的平均速度，進而得到整個流場的速度分佈。
  15. However, there are some problems in the original method, such as low availability of the extracted fragments, error position of the match results, and high complexity of the algorithm etc. in this thesis, a novel method to extract fragments is proposed, and it improves the availability of the extracted fragments ; a novel match method called her is also proposed, which is a hybrid one combining the object ’ s edge and region features, and its advancement is showed in the experimental results ; a prototypal top - down image object segmentation system named io - seg is devised and implemented in this thesis, which is based on class - specific fragment and integrates the methods proposed in this thesis

    由於csf - seg方法存在提取的子圖可用性差、匹配位置誤差大、計算復雜性高等問題，通過深入分析和研究，本文提出了一種新的提取子圖的方法，提高了產生的子圖的有效性;在深入研究匹配方法的基礎上，提出了一種新的結合對象邊緣和區域的形狀匹配方法? ? her方法，通過實驗證明了該方法的優越性;最後，結合文中提出的方法設計並實現了一個top - down的圖像對象分割原型系統io - seg 。
  16. Edges of the image are detected out firstly, labeled according to the motion that they obey then and the areas of the frame between edges are divided into regions. at last, using the bayesian framework presented determines the most likely region labeling and depth ordering with the labeled edges

    首先使用經典的canny運算元檢測出一幀圖像的邊緣，然後對其進行運動估計、邊緣和區域標定，再應用最大后驗概率的貝葉斯方法搜索出不同區域的極大似然分割，給出不同運動層的相對深度標定。
  17. Especially, the theory and character of region of interest are discussed. with maxshift method, the encoding of region of interest is implemented

    針對標準中提出的感興趣區域這一新特點，採用最大位移方法對圖像的感興趣區域進行編碼實現。
  18. Compare a lot of face image characteristic vector with face image sets characteristic matrix in order to get their similarity, and find the least value of similarity as threshold. in the detecting phase, compute the similarity between characteristic vector of testing region in gray image and face image sets characteristic matrix, if the similarity bigger or equal to threshold then the testing region is a human face, otherwise is not

    然後，用大量的人臉圖像的特徵向量與人臉圖像集特徵矩陣比較它們的相似程度，找出值小相似度，並把這個最小相似度作為閾值；在檢測階段，求出灰度圖像的待測區域的特徵向量與人臉特徵矩陣的相似度，若該相似度大於等於閾值，則是人臉，否則不是人臉。
  19. By dividing fabric image into many windows with the same size, choosing a window with minimum local entropy as a region of interest, thresholding the region and filtering out noise through opening function of mathematical morphology, calculating the defect shape factors as recognition parameters, a algorithm and method of detection of defects in fabric is studied : which has advantages of high identification, correctness, and fast inspection speed mainly because it can avoid complicated calculation of whole image and global searching when the feature parameters are extracted

    摘要將織物圖像分成大小相同的局部窗口，選取局部熵最小的窗口為待研究的感興趣區域，在此區域內分割出疵點圖像並用數學形態學中的開運算濾除噪聲，計算疵點形狀因子等作為識別參數，研究表明此方法因能避免對整幅圖像進行復雜運算，在提取特徵參數時對圖像的全局搜索，具有識別正確率高、檢測速度快等優點。
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