灰度閾值 的英文怎麼說

中文拼音 [huīdùyùzhí]
灰度閾值 英文
gray threshold
  • 灰 : Ⅰ名詞1 （物質燃燒后剩下的粉末狀的東西） ash 2 （塵土; 某些粉末狀的東西） dust 3 （特指石灰） lime...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 閾 : 名詞1. [書面語] （門坎兒） threshold; doorsill2. （界限; 范圍） threshold
  1. In course of auto - focusing, the paper takes the sum of the square of gray difference as focal distance evaluation function to decided that image is in focus or not quickly and put forward an effective auto - focus searching way based on threshold value and curve fitting. these improve speed and precision of auto - focusing

    在自動聚焦過程中，論文採用了圖象的灰度差分的絕對值之和的平方作為焦距評價函數，解決了是否正確聚焦的快速判斷問題；採用了一種行之有效的基於閾值和曲線擬合的自動聚焦搜索方式，使聚焦速度和精度都得到了很大的提高。
  2. A lot of data of elevation in different places of the shallow water of n antong were obtained by fish - exploring machine and gps determining and tide cor recting. an image which reflects landforms of nantong was obtained by selecting f rom the many noaa images on different channels and in different phases. based on the image, grey scales corresponding to different places were obtained. by using c la ssifying liner regression technique, liner regression equations were established between the elevation and grey scale, and the threshold values of grey scales of the different elevations were determined. according to the threshold values, the a reas of the tidal zone above different elevations of the shallow water of nanton g were estimated

    通過利用gps及漁探器實測，並進行潮位訂正，獲得南通淺海海域大量測點的高程資料；通過對多時相各通道noaa衛星照片進行篩選，挑選能反映淺海地貌的通道資料，從中讀取各測點相對應的灰度值，在此基礎上利用分級線性回歸，建立不同高程范圍內的高程、灰度線性回歸方程，確定不同高程的灰度閾值，從而測量出南通市淺海海域不同高程以上的潮間帶面積、分佈。
  3. Median filtering is chosen to modify the fuzzy edge by using the smoothing arithmetic, sobel operator is used to detect edge because of its filtering characteristic. image is changed from gray - scale to two - valued according to the threshold which is automaticly selected by otsu

    選用中值濾波減小平滑演算法導致的邊緣模糊;利用有濾波特性的sobel運算元進行邊緣檢測;使用最大類間方差自動確定閾值，將灰度圖像轉化為二值圖像。
  4. In this paper, we firstly design orientation filters based on directional image of fingerprint and employ them to denoise gray - scale image. then, we binarize the gray - scale image with local self - adaptive binarization smoothness algorithm and eliminate the noises from the binary image with fast fourier transform algorithm

    本文先基於指紋的方向圖設計出方向濾波器對原圖像進行濾波去噪，然後使用局部平滑閾值自適應二值化演算法，將灰度圖像進行二值化，並採用快速傅氏變換對所得到的二值化圖像進行去噪處理。
  5. Secondly, this paper mainly put forward different grey level threshold value segmentations of plane target after brief analyse the smooth and sharp image of image strengthen technology, segmentation for the overall situation, adopt the maximum variance method, the maximum entropy combine with adaptive threshold selection method, the maximum variance ration between two classes and in two classes ; segmentation for the part situation, has adopted the adaptive threshold value method ; to background more complicated segmentation, have adopted the two - dimentional maximum entropy method

    其次，在簡要的分析了圖像平滑和銳化的圖像增強技術后，重點研究了飛機目標的灰度分割，提出不同的灰度閾值分割方法進行圖像分割，對于全局分割，採用了最大類間分割法、最大熵與一致性準則相結合法、最大類間類內方差比法;對于局部分割，採用了自適應閾值法;對于背景較復雜的分割，採用了二維最大熵法。
  6. Firstly, a fourth - orders statistic hypothesis testing in inter - frame difference is used to automatically separate the moving areas from the background in a general video sequence. secondly, change areas are extracted as markers of the corresponding moving object. using the marker, region - growing algorithm can locate the precise boundary of moving object

    （ 3 ）基於輪廓跟蹤；首先介紹了提取初始模板方法?基於高次統計的判決演算法，通過選擇合適的背景噪聲閾值，最終得到較好的結果，然後對於後續幀中的邊界提取，提出將灰度圖像所使用的區域生長方法進行改進，即將它們運用到彩色圖像中，通過選擇合適的生長規則，得到較好邊界圖。
  7. Signal de - noising based on wavelet threshold method and its realize in labview

    基於最大熵的灰度閾值選取方法
  8. Object maintains several color - adjustment settings, including color - adjustment matrices, grayscale - adjustment matrices, gamma - correction values, color - map tables, and color - threshold values

    對象維護多個顏色調整設置，包括顏色調整矩陣、灰度調整矩陣、灰度校正值、顏色映射表和顏色閾值。
  9. However, most of the current wireless networks still work in low bandwidths, and mobile devices still suffer from weak computational power, short battery lifetime and limited display capability. therefore, this thesis deals with developing a very low bit - rate bi - level video coding technique, which can be used in video communications almost anywhere, anytime on any device as follows : ( 1 ) convert true color video sequences from ccd and video card to grayscale ones, ( 2 ) detect static region of successive frames by the sum of absolute differences ( sad ) and update current frame using static region of previous frame, to decrease flicker. ( 3 ) threshold the images to bi - level video sequences using ridler ' s iterative selection

    為此，本論文在傳統h . 26x和mpeg - x等視頻編解碼技術的基礎上提出了一種新的基於輪廓的視頻編解碼方案，步驟如下： （ 1 ）先把從ccd攝像頭捕捉到的視頻幀序列轉換成灰度幀序列， （ 2 ）在灰度幀序列的基礎上通過sad演算法找出相鄰幀的靜態區域，用前一幀的靜態區域更新當前幀的相應區域，這樣可以降低畫面閃爍， （ 3 ）然後用灰度直方圖迭代所產生的閾值二值化圖像，生成基於輪廓的視頻幀序列， （ 4 ）最後運用基於上下文的算術編碼技術對由第三步生成的二值化視頻幀序列進行算術編碼。
  10. Entropy of an image is to express the smoothness or homogeneity of the image. while computing in a local window, if there exist edges, the local image will not be homogenous, variation of the grayness will be sharp and the entropy obtained will be low. otherwise, the entropy will be high. given the threshold of entropy, it can be determined whether or not exist edges. because entropy operator is sensitive to noise, the effect is bad if it is directly used to detect edges. in view of the deficiency, the paper comes up with an edge detection method in which entropy operator is combined with noise removal. if the entropy computed is higher than the threshold, it will be necessary to determine whether it is caused by noise or by edges. thus edge detection and noise removal can be made at the same time. with this method satisfactory effect has been achieved by experimenting upon image with low ratio of signal to noise

    圖像的熵用來刻劃圖像的平滑性或均勻性.在圖像的局部窗口中計算時，如果窗口中存在邊界，則窗口中的圖像不均勻，其灰度變化急劇，計算出的熵小；反之熵大.設定熵的閾值，即可判斷是否存在邊界.由於熵運算元對噪聲很敏感，直接用它進行邊界檢測，效果很差.文中針對這一缺陷，提出將熵運算元與去噪相結合的邊界檢測法，如果計算出的熵大於閾值，要判斷是噪聲的出現所引起，還是邊界的出現所引起，這樣，邊檢測邊界邊去噪聲.用該方法對信噪比較低的圖像進行實驗，得到了滿意的效果
  11. The technology of automatic choose of threshold value is used, and it make the choose more reasonable. the graying arithmetic is improved in order to pick up interest point and target easily

    本文在應用部分採用了自動閾值選擇技術，使閾值的選擇更合理；對灰度化演算法進行了改進，目的是較容易的提取興趣點和目標。
  12. Pretreatment of image is studied, such as graying, smoothing, the choice of threshold value, edge detection, erosion, inflation, figure pick - up, figure following, image segmentation. the aim is to produce a breadth of image easy to recognize and understand for computer, at the same time the base is established for stereo vision

    對圖像的預處理進行了研究，如圖像的灰度化、平滑化、閾值選擇、邊緣檢測、腐蝕、膨脹、輪廓提取、輪廓跟蹤、圖像分割等，目的是產生一幅計算機易於識別和理解的圖像，同時為立體匹配奠定了基礎。
  13. Secondly, image enhancement technique based on linear filtering is adopted. a new image segmentation method by means of automatic multilevel threshold is given, which realizes partial multilevel threshold segmentation based on image region partition of gray - level position projection, removes the influence of uneven illuminance or uneven gray - level distribution on goal recognition, and resolves the problem of error segmentation caused by threshold step between adjacent regions by threshold transition. the method has well robustness

    在圖像處理時，採用基於線性濾波的圖像增強方法，並提出了一種新的自動多閾值圖像分割方法，該方法以基於灰度位置投影的圖像分區實現局部多閾值分割，克服了不均勻照明或不均勻灰度分佈對目標識別的影響，同時，通過閾值過渡很好地解決了相鄰區域閾值「階躍」引起的錯誤分割問題，具有很好的魯棒性。
  14. The robot vision is an image processing and analysis process. this paper using the common method of image fore processing currently, transforms the colorized image to gray and makes it only tow values by a critical point threshold

    機器人視覺是一個圖像處理分析過程，本文利用當前常用圖像預處理方法，對彩色圖像進行了灰度轉換、閾值分割，實現其二值化。
  15. The light spot image thresholding part of the suite puts forward the iterative algorithm to gain the best threshold by comparing, which could perfectly hold the original image feature. in the extracting the light spot image features part, the algorithms on calculating the coordinates of the " energy distribution barycenter " in the 256 gray levels image and the " geometric - center " in the binary image are adopted respectively and so on

    如在對光斑圖像進行二值化的過程中，通過比較發現使用迭代法求出最佳閾值的演算法能夠較好的保留原圖像的特徵。在對光斑圖像進行特徵提取的過程中，分別採用了對256級灰度的光斑圖像求其「能量分佈的重心」坐標；對光斑的二值化圖像求其「形心」坐標等演算法。
  16. In the image preprocessing that includes image smoothing and linear gray level transformation, the author brings forward a mended linear gray level transformation based on mean of gray value to enhance the image contrast. in the segmentation the paper presents an arithmetic taking the area of the pointers and construction feature of the water meter into consideration, which can extract the part of pointers in the special space of the water meter, and then binarizes image using a dynamic threshold based on the area of the pointer. the design can enhance the recognition rate for the next step

    在預處理中提出了一種基於灰度期望的分段線性變換；對水表的圖像分割，提出基於面積和結構信息的二值化自動分割，包括基於結構和灰度特徵的哈夫變換分割法（指針信息區的提取）和基於指針面積的特徵的閾值分割（指針提取） ；針對指針圖像的非均勻光照、背影等干擾，提出基於多特徵的分區模板匹配法對指針的方向進行識別，從而計算出讀數。
  17. Wiener method is based on statistics estimated from a local neighborhood of each pixel. ( 2 ) acquisition of head and brain volumetric data and development real head and brain reconstruction and visualization algorithms : by using threshold technique and morphological operations such as dilate and erosion, head segmented data were obtained. to obtain the brain segmented data, construct an initial template, design and developed a naval algorithm to make the initial template dynamic change with image slice to get the brain data ; designed a framework for searching, sampling and storing contour data

    採用灰度閾值技術和數學形態學的操作獲取頭的數據；在對腦的分割中，本文提出了一種根據腦圖像特點和相鄰圖像在幾何結構上具有相似性的特點，構建了自適應模板匹配檢測腦的方法：首先選擇其中最易處理的圖片應用閾值化演算法和形態學方法提取出腦輪廓，然後根據相鄰圖像之間形態具有相似性的特點，再利用形態學演算法實現腦體數據分割的操作。
  18. The algorithms employed in this paper are redesigned or improved for grid images. for example, an adaptable moving window gray scale threshold image segmentation method is proposed originally, a parallel template matching thinning algorithm is improved greatly, a sub - pixel image processing algorithm based on b - spline interpolation is present independently. 3

    其中獨立設計了自適應的移動窗口灰度閾值圖象分割法，優化設計了并行模板匹配細化演算法，獨立提出了基於三次均勻b樣條插值放大局部圖象的亞象素圖象處理演算法，並都取得了較好的處理效果。
  19. Next, edge detection using differential operator, edge thinning and connecting are introduced. model and methods of image segmentation are discussed subsequently. stereo matching methods, such as correlative matching algorithm and least squares matching algorithm are given and realized

    本文針對圖像的灰度和邊緣等特徵，研究了微分運算元邊緣檢測方法以及邊緣細化和連接的演算法，給出了圖像分割的模型和灰度閾值的簡單分割及自動分割方法。
  20. Those algorithms can be categorized into those based on intensity segmentation and those based on color segmentation

    演算法進一步分為基於灰度閾值分割和基於彩色分割的演算法。
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