texture segmentation造句
造句與例句
手機(jī)版
- Texture segmentation with wavelet transform and feature weighting
利用小波變換和特征加權(quán)進(jìn)行紋理分割 - ( 6 ) we have studied the methods of image texture segmentation systematically
6 、基于遙感圖像紋理分割方法的研究。 - Texture segmentation of multispectral remote sensing image based on markov random field
基于馬爾柯夫隨機(jī)場(chǎng)的多波段遙感影像紋理分割研究 - Using those features , texture segmentation algorithms are presented and tested on natural images
最后，我們?cè)谏鲜龌A(chǔ)上給出了相應(yīng)的紋理圖像分割算法。 - The texture segmentation method which based on the self - adapted texture windows selected is proposed
提出了通過(guò)不同的紋理窗口的選擇來(lái)自適應(yīng)的完成紋理的分割。 - The arithmetic that aims at the problems of texture segmentation is improved and the experiments have been done
針對(duì)紋理分割過(guò)程中存在的一些問(wèn)題，對(duì)算法進(jìn)行了改進(jìn)，并進(jìn)行了仿真實(shí)驗(yàn)。 - Finding more useful texture segmentation methods and the research about the parallel image processing are regarded as a solution to the problem
引入有針對(duì)性的分割方法，與進(jìn)行并行處理為這個(gè)問(wèn)題的解決提供了一條有效的途徑。 - 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(shí)別中一個(gè)重要的研究?jī)?nèi)容,一直以來(lái)是人們研究的熱點(diǎn)。 - 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(wèn)題是紋理分割，紋理特征的提取和特征的分類是紋理分割的關(guān)鍵。 - We discussed the techniques of image texture segmentation in details , and compared the differences . finally , we pointed out the main problems in existing methods
對(duì)遙感圖像的紋理分割技術(shù)進(jìn)行了詳細(xì)討論，然后對(duì)常用的紋理分割方法進(jìn)行了分析比較，并提出了現(xiàn)有方法存在的主要問(wèn)題。 - It's difficult to see texture segmentation in a sentence. 用texture segmentation造句挺難的
- The main work that have been done as follows : ( 1 ) through the comparison of different fractal dimension , we find that the improved box - counted dimension and brownial fractal dimension fit texture segmentation
本文的主要工作如下： ( 1 )通過(guò)對(duì)不同分形維數(shù)的比較可知，改進(jìn)的盒子維數(shù)和分形布朗維數(shù)較適合紋理的描述。 - 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(jù)j . c . nunes等人提出的bemd的基本思想,進(jìn)行了一定的改進(jìn),實(shí)現(xiàn)了基于bemd方法的圖像無(wú)參數(shù)分解、紋理分割和圖像降噪,取得了不錯(cuò)的效果。 - 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(jié)合遙感影像中面狀目標(biāo)的紋理特征，深入分析了前人提出的三種紋理分割模型，并結(jié)合居民地的特點(diǎn)提出了基于幾何結(jié)構(gòu)信息的紋理分割模型。 - 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(duì)局部二進(jìn)制模板紋理分割速度較慢的問(wèn)題,本文一方面調(diào)整了模板算子的計(jì)算方式,另一方面將單一門限的區(qū)域合并改進(jìn)為雙門限合并。 - Texture segmentation involves accurately partitioning an image into sections according to the textured regions or by recognizing the borders between different textures in the image . texture feature extraction is crucial in the texture segmentation
它是依據(jù)同一紋理的一致性特征或不同紋理之間的特征差別,將紋理圖像分割成若干有意義的區(qū)域,而提取有效的紋理特征是其中的關(guān)鍵和難點(diǎn)。 - In the aspect of relationship between algorithms and objects , we begin with the adaptive color and texture segmentation for tracking moving objects , then analyze the weakness of original algorithm flow and give an improved method to its structure
本文通過(guò)對(duì)視頻目標(biāo)跟蹤整體流程的研究，分析自適應(yīng)的顏色和紋理組合分割算法，并對(duì)算法在流程上由于多個(gè)環(huán)節(jié)的綁定而導(dǎo)致的算法設(shè)計(jì)的不靈活性進(jìn)行改進(jìn)。 - 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(guó)內(nèi)外技術(shù)發(fā)展概況，介紹了基于統(tǒng)計(jì)和空間頻域的紋理特征提取方法以及基于模糊聚類神經(jīng)網(wǎng)絡(luò)的分割算法。 - For the object segmentation in textured background , a feature image segmentation algorithm is proposed according to the difference of texture energy distribution between textured background and objects in wavelet channels . then , the algorithm is modified to apply to texture segmentation and object segmentation in multi - textured background . it is showed that the algorithm gives a good feature representation not only between different textures but also texture and objects . and the correct segmentation result are obtained in our experiments . the dissertation consists of five chapters
本文將小波分析這個(gè)數(shù)學(xué)工具引入到圖象分割中，在深入研究小波變換特點(diǎn)的基礎(chǔ)上，在小波標(biāo)架下對(duì)紋理作出了定性的分析，針對(duì)紋理背景下的物體分割，根據(jù)紋理背景和目標(biāo)物體經(jīng)小波分解后各個(gè)通道的紋理能量值的不同分布，提出了特征圖象分割算法，并將它改進(jìn)用于紋理圖象的分割及多紋理背景下的物體分割。 - The experiments on the images of triangle , rectangle and plane approve the correctness and validity of line segment method . 4 chapter four is devoted to summarize moment applications in the fields of image processing , computer vision , and pattern recognition . these applications mainly include scene matching , histogram matching , image reconstruction , image compression , symmetry detection , image normalization , texture segmentation , edge detection , aircraft recognition , and image indexing , etc .
4 、綜述了矩技術(shù)在圖像處理、計(jì)算機(jī)視覺(jué)、和模式識(shí)別領(lǐng)域內(nèi)的應(yīng)用，主要包括：景物匹配、直方圖匹配、圖像重建、圖像壓縮、對(duì)稱性檢測(cè)、圖像規(guī)格化、紋理分割、邊緣檢測(cè)、飛機(jī)識(shí)別和圖像檢索等等。 - 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
該算法有效的利用了由灰度共現(xiàn)陣得到的、不同分辨率上最能表述紋理特性的統(tǒng)計(jì)特征,分層次對(duì)圖像進(jìn)行分割,然后結(jié)合紋理的結(jié)構(gòu)信息對(duì)邊緣區(qū)域進(jìn)行邊界定位,進(jìn)而得到較準(zhǔn)確的紋理分割圖。
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