fuzzy texture 中文意思是什麼
fuzzy texture
解釋
絨毛狀網紋-
( 2 ) a new minutiae verification method based on the fuzzy geometry features and texture features is proposed
（ 2 ）提出了一種新的基於模糊幾何特徵和紋理特徵的細節點驗證方法。 -
In this paper, combined with vanishing point geometrical restriction given by the aerial photogrammetric modeling, a method for extracting vertical lines based on the adaptive fuzzy hough transform is presented. then the extracted vertical lines are validated by analyses of window texture
本文結合航空攝影模型給出的滅點幾何約束，利用自適應模糊hough變換，提出了一種建築物垂直邊緣檢測方法，並用窗戶紋理分析技術來驗證高層建築物的垂直邊緣。 -
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。 -
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。 -
Firstly take the local neighbor area of a minutia in the gray image. then analyze the fuzzy geometry features and texture features in the local area and use these features as the input of a mlp neural network to realize the classification of true and spurious minutiae
取細節點在原始灰度圖象上的局部鄰域，分析鄰域中的模糊幾何特徵和紋理特徵，以這些特徵作為mlp神經網路的輸入，實現細節點的真假驗證。 -
In this paper, we first established the image metadata used in our system which based on the famous dublin core, then we analyzed the abstraction and description visual features of image such as color texture and shape. next, we discussed the problem of similarity measure of visual feature, imported fuzzy logic into the distance feature and pointed out the disadvantages of geometry space based methods. for multi - dimension vector ' s high dimension nature, it ' s hard to index with traditional methods, we discussed how to lower the dimension using clustering and klt transformation
本文首先在dublincore的基礎上制定了適合我們要求的圖像元數據集；詳細分析了顏色、紋理、形狀等視覺特徵的提取和表示方法；探討了圖像視覺特徵相似度量的問題，將模糊技術引入直方圖的距離度量，分析了幾何空間距離度量函數的不足之處，提出了系統中採用的距離函數；針對圖像視覺特徵向量的多維特性，分析了現有的各種降維技術和多維索引技術。 -
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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