texture segmentation 中文意思是什麼

texture segmentation 解釋
紋理分割
  • texture : n 1 （織物的）組織，結構，質地，織法。2 織品，織物。3 （皮膚的）肌理；（巖石、木材等的）紋理。4 ...
  • segmentation : n. 1. 分割；切斷。2. 【生物學】（細胞）分裂；（動物）分節；斷裂。
  1. Texture image segmentation based on gaussian mixture models

    基於高斯混合模型的紋理圖像分割
  2. 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。
  3. Figs 4. 3 and 4. 4 show examples of segmentation by texture or context.

    圖43和圖44給出了根據紋理或質地進行分割的例子。
  4. Texture segmentation with wavelet transform and feature weighting

    利用小波變換和特徵加權進行紋理分割
  5. ( 6 ) we have studied the methods of image texture segmentation systematically

    6 、基於遙感圖像紋理分割方法的研究。
  6. Texture segmentation of multispectral remote sensing image based on markov random field

    基於馬爾柯夫隨機場的多波段遙感影像紋理分割研究
  7. The arithmetic that aims at the problems of texture segmentation is improved and the experiments have been done

    針對紋理分割過程中存在的一些問題，對演算法進行了改進，並進行了模擬實驗。
  8. The rnultiscale edge detection and texture image segmentation are studied based on the variogram function

    我們基於變差函數的這種性質對圖像的多尺度邊緣檢測和紋理分割作了較為深入的研究。
  9. As an important aspect of digital image process and pattern recognition, texture segmentation has always been one of the hottest and most difficult study topics

    紋理分割是圖像處理和模式識別中一個重要的研究內容，一直以來是人們研究的熱點。
  10. Texture segmentation is an important and difficult problem in the texture analysis ; texture feature extraction and classification are crucial in the texture segmentation

    紋理分析中一類重要且難度較大的問題是紋理分割，紋理特徵的提取和特徵的分類是紋理分割的關鍵。
  11. The multiscale modeling we describe in this dissertation has been employed in a wide variety of applications, including : geophysical remote sense imaging, ocean height estimation, surface reconstruction, image denoising, texture discrimination, image segmentation, object recognition and multisensor fusion for groundwater hydrology

    目前，多尺度模型技術已在地形遙感成像、海洋高度估計、地表重構、圖像去噪、紋理辨識、圖像分割、目標識別和地下水文學的多傳感器數據融合等實際問題中得到了廣泛的應用。
  12. 3. three texture segmentation models are analyzed thoroughly combined with basic characteristics of region target and a texture segmentation model is presented according to the character of residential areas. 4

    結合遙感影像中面狀目標的紋理特徵，深入分析了前人提出的三種紋理分割模型，並結合居民地的特點提出了基於幾何結構信息的紋理分割模型。
  13. The texture segmentation method which based on the self - adapted texture windows selected is proposed

    提出了通過不同的紋理窗口的選擇來自適應的完成紋理的分割。
  14. In this thesis, we improve the bemd method which is introduced by j. c. nunes et al. our approach has good effects in texture segmentation, image denoising and image decomposition without parameter

    本文根據j . c . nunes等人提出的bemd的基本思想，進行了一定的改進，實現了基於bemd方法的圖像無參數分解、紋理分割和圖像降噪，取得了不錯的效果。
  15. Using those features, texture segmentation algorithms are presented and tested on natural images

    最後，我們在上述基礎上給出了相應的紋理圖像分割演算法。
  16. This paper takes the high spacial - differentiating remote sensing image material as research objects, studies and realizes four feature - oriented image segmentation methods : orient phase method, fuzzy threshold with genetic algorithms method, gaussian markov random field model texture segmentation method and moment feature - based texture segmentation, analyses their fundamental theories, their merits and drawbacks in detail, and validates them by some experiments

    本文以高空間解析度的遙感資料為對象，研究和實現了四種面向特徵的圖像分割演算法：方向相位法、結合遺傳演算法思想的模糊閾值分割方法、基於高斯馬爾科夫隨機場模型的紋理圖像分割方法和基於矩特徵的紋理圖像分割方法，詳細分析了它們的原理和各自的優缺點，並用具體實驗進行了驗證。
  17. Secondly, texture segmentation based on local binary pattern ( lbp ) texture descriptor is very time consuming. for one thing, we adjust the computing method of lbp, for another, set two merging threshold instead of only one

    第二，針對局部二進制模板紋理分割速度較慢的問題，本文一方面調整了模板運算元的計算方式，另一方面將單一門限的區域合併改進為雙門限合併。
  18. The significance, the function and the development of texture segmentation are discussed in this paper. the statistical and the space / frequency methods of feature extraction, segmentation methods based on fuzzy clustering neural networks are discussed also

    本論文全面論述了紋理圖像分割的意義、作用及國內外技術發展概況，介紹了基於統計和空間頻域的紋理特徵提取方法以及基於模糊聚類神經網路的分割演算法。
  19. It also presents a hybrid approach on the basis of the synergetic network and texture spectrum, which utilizes the advantages of both the top - down synergetics and the traditional down - to - top classifying methods to construct the multi - classifier. the first level classifier is based on snn, in which a novel prototype selection algorithm on the basis of texture features instead of pixels is presented and the second level the texture segmentation algorithm based on the global texture spectrum. finally, it tests the multi - classifier with a great

    在筆跡鑒別多分類器模型的構造中，本文將協同神經網路與紋理譜概念相結合，由自上而下的協同方法和自下而上傳統分類識別方法相結合構造多分類器，第一層分類器基於協同神經網路，其中，在原型模式的選擇演算法上，本論文提出了用紋理特徵替代象素的協同模式識別演算法；第二層分類器基於全局紋理譜的紋理分割演算法。
  20. Based on fuzzy clustering algorithm, we studied the objective function of the traditional fuzzy c - means algorithm and proposed a modified objective function for fcm ; we discussed clustering validity problem, and a texture segmentation method based on adaptive fcm has been constructed by the guidance of fuzzy clustering validity

    在介紹聚類演算法的基礎上，研究了模糊c -均值聚類演算法目標函數的改進問題，提出了基於修正目標函數的fcm演算法；討論了聚類有效性問題，在模糊聚類有效性函數指導下構造了一種自適應模糊c -均值聚類演算法的紋理分割方法。
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