特徵分割 的英文怎麼說

中文拼音 [tèzhǐfēngē]
特徵分割 英文
feature division
  • 特 : Ⅰ形容詞（特殊; 超出一般） particular; special; exceptional; unusual Ⅱ副詞1 （特別） especially; v...
  • 徵 : 名詞[音樂] （古代五音之一 相當于簡譜的「5」） a note of the ancient chinese five tone scale corre...
  • 分 : 分Ⅰ名詞1. （成分） component 2. （職責和權利的限度） what is within one's duty or rights Ⅱ同 「份」Ⅲ動詞[書面語] （料想） judge
  • 割 : 動詞（截斷） cut; mow
  • 特徵 : characteristic; feature; properties; aspect; trait
  1. The retinal image segmentation, the feature points of blood vessel extraction, the feature correspondency, the transformation model of retinal image and the registration parameter optimizing methods are all the main facts studied in the paper

    主要研究內容包括視網膜圖像血管網路的分割、血管特徵點的提取、特徵對應性、變換模型以及參數優化等方面。
  2. First the sketch / datum plane is fitted by least - square distance, then the extruded direction or axis with the flank points of the cloud is extracted in quadratic paogramming arithmetic, and certain points projected to gain 2d sketched datas. feature points are defined to segment the sketch datas, and the sketch profile is generated by fitting separately the line and circle segment

    使用最小二乘方法擬合草圖基準平面，採用二次規劃方法提取拉伸方向和旋轉軸線，然後將數據點投影以獲取草圖數據，通過柵格劃分提取草圖邊界輪廓數據，再對這些邊界數據進行基於特徵點的分割，以直線和圓弧段擬合出草圖輪廓。
  3. Using the way combining the mathematic morphology top - hat and gauss matched filtering can effectively reduce the influence of the inherent fovea and the marginal noise brought forth by the retinal camera caliber in retinal image and increase the precision of retinal image segmentation and feature point extraction

    文中提出了採用灰度數學形態學中的top - hat變換和高斯匹配濾波相結合的方法，用來有效的降低視網膜熒光圖像中固有的小窩現象及眼底照相機的口徑所引起的視網膜圖像邊界像素噪聲，極大的提高了圖像分割及特徵提取的精度。
  4. In this paper, we made an investigation into texture feature extraction and classification based on statistic method and its application in multi - spectral image classification. the research works of this paper have been done as follows : firstly, in order to overcome the weakness of gray level co - occurrence matrix ( glcm ), a new unsupervised texture segment algorithm, based on multi - resolution model, is presented in this thesis

    本文主要研究了基於紋理統計特性的特徵提取與分割方法，並將其用於實際的多光譜圖像分類，具體工作如下:第一，針對傳統灰度共現陣方法中特徵提取的尺度單一問題，本文提出了一種多分辨無監督紋理分割演算法。
  5. It first finds the best features that are extracted from glcm and explain the texture clearly in different resolution, and then segments on different level, at last, by combining the structure information of texture edge, extract the edge of different patterns to get a relatively accurate result of texture segmentation

    該演算法有效的利用了由灰度共現陣得到的、不同解析度上最能表述紋理特性的統計特徵，分層次對圖像進行分割，然後結合紋理的結構信息對邊緣區域進行邊界定位，進而得到較準確的紋理分割圖。
  6. Secondly, in the feature extraction stage, haar 2 - d wavelet transform is used in each band of the normalized image. the mean values and variances of the coefficients of 7 main wavelet channels are extracted as features

    該演算法通過對歸一化處理后虹膜圖像的各個小分割區域進行二維小波變換，提取出主要小波通道的小波系數均值和方差作為特徵值。
  7. Secondly, the steps of the glass ' s image processing are discussed in detail. based on the experiments and the characteristics of interference fringe, we pre - process the images with median filter and image segmentation with dynamic threshold. after marking and thinning the resulted fringes, we analyze linearly the unifor mity of product ' s samples with the characteristics of the framework

    然後，結合檢測系統中玻璃干涉圖像處理的任務，詳細介紹了處理的各個步驟：通過實驗比較，並結合干涉條紋圖像的特點，選擇中值濾波、動態閾值分割等技術對圖像進行預處理；然後對獲得的二值條紋進行標記、細化，提取條紋骨架；最後，用骨架的特徵進行線性分析，識別條紋的類型，判斷玻璃樣品的均勻性。
  8. We provide the structure and function of system software and hardware, discuss image attaining, division employee serial number from chest card image, then combine multiple characteristic and coding to recognize employee serial numbe, employee identity, and register check on work attendance

    文中給出基於胸卡識別的?勤系統的體系結構和功能，並詳細論述了圖像捕捉、胸卡和編號的分割、以及採用多特徵抽取和編碼器結合對編號進行識別的方法，進行職工身份識別，達到?勤的目的。
  9. The correctness is over 99 %. ( 5 ) shape features studied were aspect, first invariant central moment, elongatedness, roundness, circularity and thickness. aspect and first invariant central moment are the most effective shape features for identifying monocotyledonous weed from dicotyledonous weed, and the correctness was 93 %

    （ 4 ）利用修正的色度公式，由判別分析法確定色度閾值，對雜草圖像進行閾值分割，能夠有效地識別植物與非植物背景，正確識別率在99以上，但色度的計算量大於過綠特徵的計算量，不利於雜草識別速度的提高。
  10. This dissertation deals with the content - based image retrieval ( cbir ) theory and technique ; some new features and tools for more concisely and discriminatingly charactering the content of an image are proposed, such as region - based color histogram, grey - primitive co - occurrence matrix, ratio of centripetal moment, ratio of eccentric moment and ratio of inertial moment. a new modified genetic algorithm is also described in this dissertation, which can upgrade the performance of standard genetic algorithm ( sga ) while used in image segmentation

    本文以圖像數據庫檢索為主線，討論了基於視覺內容的圖像檢索方法，提出包括基於區域顏色直方圖、灰度?基元共生矩陣及向心矩比、偏心矩比、慣性矩比的特徵描述方式；對遺傳演算法存在的早熟、收斂到最優解慢等問題提出了解決方法，並將改進遺傳演算法應用到圖像分割中，編制了相應程序。
  11. This paper makes a good study of the face recognition, including testifying the face from an image, partitioning main area of the face, abstracting the edge of the image, locating the characteristic points, recognizing the same face, etc. i have many new ideas in the study as follows : a method partitioning facial area from an image by 24 _ bit color is described

    本論文對人臉識別技術的演算法作了全面的研究，包括對圖像進行人臉的檢測、區域分割、邊緣提取、去除噪聲和特徵點的定位、特徵向量的提取、識別等這幾個部分。提出了如下幾種實用和有效的演算法：在對當前多種人臉檢測方法的研究后，提出了一種利用膚色對面部圖像進行分割的方法。
  12. Effective feature analysis for color image segmentation

    用於彩色圖像分割的有效特徵分析
  13. Secondly, feature extraction methods based on target profile is researched. for segmented target, fourier descriptor is adopted

    其次，研究了用於目標輪廓信息特徵提取的方法;對已分割的目標提取輪廓信息，採用傅立葉描述符描述。
  14. The multiscale mixed distribution models ( mmdm ) and the multiscale autoregressive ( mar ) models are investigated in this thesis, and they are applied to the unsupervised segmentation of the synthetic aperture radar ( sar ) image by joining them together - the multiscale mixed distribution models as the feature extractor and the multiscale autoregressive models as the classifier

    本文對多尺度混合分佈模型（ multiscalemixturedistributionmodels簡記mmdm ） ，其中主要是對多尺度混合gauss分佈模型（ multiscalemixturegaussianmodels簡記mmgm ）和多尺度混合rayleigh分佈模型（ multiscalemixturerayleighmodels簡記mmrm ）進行了研究，及對多尺度自回歸（ multiscaleautoregressive簡記mar ）模型進行了研究，並將mmdm作為圖像分割的分類器， mar模型作為圖像分割的特徵提取器對合成孔徑雷達（ syntheticapertureradar簡記sar ）圖像無監督分割進行了研究。
  15. This two kinds of methods make a good use of the information supplied by multiple - dimensional feature space and enhance the accuracy of segmentation

    這兩種方式有效地利用了多維特徵空間對于分割目標所提供的信息，使分割的準確性有了較大的提高。
  16. In this paper, the contrast of original image is enhanced by nonlinear transformation based on the characteristics of grain image ; after comparing several methods of threshold segmentation and analyzing their performance and applicability on grain image, the adaptive threshold segmentation based on gradient image is presented ; the noise of binary image is reduced with morphological filter, the hollow in binary image is filled in and a recognition algorithm is designed to remove agglomerate particle ; on the basis of mathematical morphology two methods are adopted to segment agglomerate grains that are not agglomerated tightly ; the parameters of size and shape, perimeter, area, diameter, complexlity, longest feret diameter, shortest feret diameter etc, are extracted. this technique is applied in measurement of pearl powder ' s particle size

    本文根據粒度圖像的特點，採用非線性對比度增強處理改善顆粒顯微圖像的對比度；對多種閾值分割方法進行比較，分析了它們的性能和用於粒度圖像的適用性，在此基礎上提出了一種基於梯度圖像的動態閾值分割方法；對獲取的顆粒二值圖像進行形態濾波和空洞填充，設計了識別演算法去除凝聚體；對重疊不太嚴重的粘結顆粒採用了兩種基於數學形態學的分割演算法；提取了周長、面積、粒徑、復雜度、最長feret徑、最短feret徑等大小和形狀特徵參數，對珍珠粉等粉體粒度進行了測量。
  17. In this paper, the part of apis based on minutia features includes mainly computing orientation, filtering, binarization, thinning, feature extraction, postprocessing and minutia matching ; the part of apis based on statistical features is composed of reference point location, extracting feature, classification and matching. some new approaches are brought forward : 1 ) in the preprocessing, a new binarization method of fingerprint images based on the orientation and the dynamic threshold is proposed, which has the excellent capability of noise resistance. this method makes fully use of the orientation and the characteristics of grayscale change, gets the binarized images from the primitive fingerprint images directly, instead of the series of processing such as smoothing, enhancement and binarization

    本論文對這兩種系統做了深入地研究，從基於細節點特徵的系統中求取指紋方向圖? ?濾波? ?二值化? ?細化? ?特徵提取? ?后處理，到基於統計性特徵的系統中選取指紋圖像參考點? ?提取統計性特徵? ?分類? ?匹配等環節，都一一進行了討論，並提出了一些新方法： 1 ）在基於細節點特徵系統的預處理部分，本論文提出一種新的基於方向圖具有動態閾值的指紋圖像二值化方法，這種演算法能夠在保持特徵點不丟失的基礎上一次性完成一般指紋圖像處理中的無效塊分割、增強、濾波、二值化的過程。
  18. Therefore, in recent years, people bring out the image expression and the research method based on moving object, which lay emphasis on the understanding of the main object and the analysis of the video content

    這種基於對象的檢索對圖像不再限於紋理、色彩、形狀等區域性質，對視頻不只是視頻序列的鏡頭分割或句法特徵分析，而是基於圖中的主體對象和視頻的語義分割。
  19. Document analysis and chinese character segmentation are two important parts of ocr system. the former segments the document image into several parts and distinguishes the parts text, image, drawing or table etc. we call them the parts blocks. the blocks got by document analysis will be different treated

    版面分析與字元切分是ocr系統的兩個重要組成部分，前者是將文檔圖象按一定特徵分割成文本、圖象、圖形或表格等版面基元，各個基元在後續處理中將採用不同處理方法。
  20. The eyes can be considered as a salient and relatively stable feature of faces, so firstly eyes - analogue regions in cluttered images are segmented using local adaptive threshold edge detector. then the small eye - analogue regions are grouped together and labeled using a traditional labeling process according to their geometrical and color features. instead of finding potential eye - pairs from eye - analogue regions one by one, all possible pairs of eyes are encode as the solution, and the potential face are searched by gas

    新意之處：利用膚色是一種感知現象的特性以及神經網路的強大感知、學習功能，採用進化神經網路對膚色進行感知和分類；以眼睛的幾何和周邊的膚色特徵分割眼睛塊，克服了在完整的膚色區域內檢測人臉方法的局限性；對候選眼睛對的編號而不是人臉在圖像中的位置、人臉的尺度和方向進行編碼，使遺傳演算法用於人臉定位時的問題空間得以大大簡化，採用一個新穎的眼睛及臉頰部位的灰度投影及膚色模板驗證，可以實現多尺度、任意方向的正面人臉檢測，實驗結果令人滿意。
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