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紋理特征提取方法綜述
電子技術(shù)應(yīng)用 2023年6期
袁艷鵬,汪宇玲
(東華理工大學(xué) 信息工程學(xué)院,江西 南昌 330000)
摘要: 圖像紋理特征提取是圖像紋理分類與分割的基礎(chǔ),,廣泛應(yīng)用于醫(yī)學(xué)圖像,、遙感圖像等領(lǐng)域。對近期的主流紋理特征提取方法以及融合方法進(jìn)行了分析與總結(jié),,并探討了紋理特征提取方法未來的研究方向,。首先詳細(xì)介紹了12個主流的公開紋理數(shù)據(jù)集的特點(diǎn)及其適用場景;接著總結(jié)了近幾年出現(xiàn)的一些紋理特征提取方法,,并根據(jù)特征融合方式從多個角度對紋理特征融合方法進(jìn)行了分類介紹,;最后總結(jié)了紋理特征提取存在的難點(diǎn)和挑戰(zhàn),并對未來的紋理特征提取方法研究方向進(jìn)行思考和討論,。
中圖分類號:TP391.4
文獻(xiàn)標(biāo)志碼:A
DOI: 10.16157/j.issn.0258-7998.223659
中文引用格式: 袁艷鵬,,汪宇玲. 紋理特征提取方法綜述[J]. 電子技術(shù)應(yīng)用,2023,,49(6):9-17.
英文引用格式: Yuan Yanpeng,,Wang Yuling. A review of texture feature extraction methods[J]. Application of Electronic Technique,2023,,49(6):9-17.
A review of texture feature extraction methods
Yuan Yanpeng,,Wang Yuling
(School of Information Engineering, East China University of Technology,, Nanchang 330000,,China)
Abstract: Image texture feature extraction is the basis of image texture classification and segmentation, and is widely used in medical images, remote sensing images and other fields. The recent mainstream texture feature extraction methods and fusion methods are analyzed and summarized, and the future research direction of texture feature extraction methods is discussed. Firstly, the characteristics of 12 mainstream public texture datasets and their applicable scenarios are introduced in detail. Then, some texture feature extraction methods that have emerged in recent years are summarized, and the texture feature fusion methods are classified from multiple angles according to the feature fusion methods. Finally, the difficulties and challenges of texture feature extraction are summarized, and the research direction of texture feature extraction methods in the future is considered and discussed.
Key words : texture feature extraction;texture feature fusion,;texture dataset,;deep learning

0 引言

自20世紀(jì)60年代以來,許多研究者開始對圖像的紋理分析研究,。紋理特征是圖像的重要特征,,在圖像識別中發(fā)揮重要的作用。對于人類視覺來說,區(qū)分紋理并不困難,。但目前對于紋理還沒有一個明確的定義,,一般認(rèn)為它是由許多相互關(guān)聯(lián)且周期性重復(fù)的單元構(gòu)成的。紋理具有局部序列性不斷重復(fù),、非隨機(jī)排列,、紋理區(qū)域內(nèi)大致均勻等特點(diǎn)。



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作者信息:

袁艷鵬,,汪宇玲

(東華理工大學(xué) 信息工程學(xué)院,,江西 南昌 330000)


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