可變光照下的唇讀識別技術(shù)研究
發(fā)布時間：2018-11-02 19:43
【摘要】：唇讀技術(shù)擁有重大的研究價值和極為廣泛的應(yīng)用前景。近年來越來越多的唇部定位和唇動識別算法被提出,然而這些算法的研究主要局限在正面理想光照條件下,而實際的唇讀識別系統(tǒng)都將工作在光照變化的應(yīng)用環(huán)境中。因此,本文致力于可變光照環(huán)境下的唇讀識別技術(shù)研究,以減弱外部光照對唇讀造成的影響,提高唇部定位和唇動特征提取算法的魯棒性。唇讀數(shù)據(jù)庫是本文展開研究的基石。為此,本文首先對國內(nèi)外已有的唇讀數(shù)據(jù)庫進行了研究和對比,以借鑒其建庫的方法和思路。在此基礎(chǔ)上,針對本課題的需要建立了光照可變的唇讀數(shù)據(jù)庫以用于后續(xù)研究。為了準確的定位和分割唇部區(qū)域,本文設(shè)計了一種三段式唇部定位算法。首先采用Haar-like特征和Ada Boost算法定位人臉,在此基礎(chǔ)上根據(jù)人臉固有的結(jié)構(gòu)特征對唇部進行粗定位,對于最后的唇部精確分割,本文提出了一種基于HSV顏色空間H分量的分割算法。實驗證明,本文所提方法在光照可變的環(huán)境下仍可準確的定位唇部區(qū)域。為了減弱外部光照變化對唇動特征提取造成的影響,本文從去光照預(yù)處理和提取光照不變特征兩個方面來增強唇動特征提取算法的魯棒性。本文設(shè)計的去光照預(yù)處理鏈由中值濾波、Gamma校正、多尺度Retinex濾波和對比度均衡化構(gòu)成。經(jīng)過該預(yù)處理算法處理可有效濾除部分光照噪聲。在此基礎(chǔ)上,本文通過對傳統(tǒng)LBP特征提取算法進行拓展改進,對唇部提取了改進的LBP直方圖特征。該特征具有一定的光照不變性,可進一步提高可變光照下的唇讀識別率。本文采用SVM算法進行唇動識別。針對SVM算法只能進行二分類的缺陷,本文采用了一對一的推廣策略使其能識別多個詞匯;對于SVM算法要求輸入特征向量維度固定的問題,本文設(shè)計了唇動特征序列長度規(guī)整算法將其規(guī)整為統(tǒng)一的維度。最后基于SVM算法分別在自然光照和可變光照不同條件下驗證了所提的唇動特征提取算法的合理性和有效性。
[Abstract]:Lip reading technology has great research value and wide application prospect. In recent years, more and more lip localization and lip motion recognition algorithms have been proposed. However, the research of these algorithms is mainly confined to the positive ideal illumination condition, and the actual lip reading recognition system will work in the application environment of illumination change. Therefore, in order to reduce the influence of external illumination on lip reading and improve the robustness of lip location and lip feature extraction algorithms, this paper focuses on lip recognition technology in variable illumination environment. Lip-reading database is the cornerstone of this paper. Therefore, this paper first studies and compares the existing lip reading databases at home and abroad in order to draw lessons from the methods and ideas of building them. On this basis, the database of lip reading with variable illumination was established to meet the needs of the subject. In order to locate and segment lip region accurately, a three-segment lip location algorithm is designed in this paper. Firstly, the Haar-like feature and Ada Boost algorithm are used to locate the face, and then the lip is roughly located according to the inherent structural features of the face, and the final lip is segmented accurately. In this paper, a segmentation algorithm based on H component in HSV color space is proposed. Experiments show that the proposed method can accurately locate the lip region in the environment of variable illumination. In order to reduce the influence of external illumination on lip feature extraction, this paper improves the robustness of lip feature extraction algorithm from two aspects: removing illumination preprocessing and extracting illumination invariant feature. The de-illumination preprocessing chain is composed of median filter, Gamma correction, multi-scale Retinex filter and contrast equalization. The preprocessing algorithm can effectively filter part of the illumination noise. On this basis, the traditional LBP feature extraction algorithm is extended and improved, and the improved LBP histogram feature is extracted from the lip. The feature has certain illumination invariance, which can further improve the recognition rate of lip reading under variable illumination. In this paper, SVM algorithm is used for lip recognition. Aiming at the defect that SVM algorithm can only be classified into two categories, a one-to-one generalization strategy is adopted in this paper so that it can recognize more than one vocabulary. For the problem that the SVM algorithm requires the input feature vector dimension to be fixed, this paper designs the lip motion feature sequence length regularization algorithm to make it a unified dimension. Finally, based on the SVM algorithm, the rationality and effectiveness of the proposed lip feature extraction algorithm are verified under different conditions of natural illumination and variable illumination, respectively.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41
本文編號：2306769
[Abstract]:Lip reading technology has great research value and wide application prospect. In recent years, more and more lip localization and lip motion recognition algorithms have been proposed. However, the research of these algorithms is mainly confined to the positive ideal illumination condition, and the actual lip reading recognition system will work in the application environment of illumination change. Therefore, in order to reduce the influence of external illumination on lip reading and improve the robustness of lip location and lip feature extraction algorithms, this paper focuses on lip recognition technology in variable illumination environment. Lip-reading database is the cornerstone of this paper. Therefore, this paper first studies and compares the existing lip reading databases at home and abroad in order to draw lessons from the methods and ideas of building them. On this basis, the database of lip reading with variable illumination was established to meet the needs of the subject. In order to locate and segment lip region accurately, a three-segment lip location algorithm is designed in this paper. Firstly, the Haar-like feature and Ada Boost algorithm are used to locate the face, and then the lip is roughly located according to the inherent structural features of the face, and the final lip is segmented accurately. In this paper, a segmentation algorithm based on H component in HSV color space is proposed. Experiments show that the proposed method can accurately locate the lip region in the environment of variable illumination. In order to reduce the influence of external illumination on lip feature extraction, this paper improves the robustness of lip feature extraction algorithm from two aspects: removing illumination preprocessing and extracting illumination invariant feature. The de-illumination preprocessing chain is composed of median filter, Gamma correction, multi-scale Retinex filter and contrast equalization. The preprocessing algorithm can effectively filter part of the illumination noise. On this basis, the traditional LBP feature extraction algorithm is extended and improved, and the improved LBP histogram feature is extracted from the lip. The feature has certain illumination invariance, which can further improve the recognition rate of lip reading under variable illumination. In this paper, SVM algorithm is used for lip recognition. Aiming at the defect that SVM algorithm can only be classified into two categories, a one-to-one generalization strategy is adopted in this paper so that it can recognize more than one vocabulary. For the problem that the SVM algorithm requires the input feature vector dimension to be fixed, this paper designs the lip motion feature sequence length regularization algorithm to make it a unified dimension. Finally, based on the SVM algorithm, the rationality and effectiveness of the proposed lip feature extraction algorithm are verified under different conditions of natural illumination and variable illumination, respectively.
【學位授予單位】：哈爾濱工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41
【參考文獻】
相關(guān)期刊論文 前10條
1 張澤梁;宋紹成;張滴石;曹健;;基于Fourier描述子的唇形分類方法[J];吉林大學學報(理學版);2015年01期
2 張澤梁;楊成佳;宋紹成;;唇讀研究進展綜述[J];計算機工程與設(shè)計;2014年06期
3 徐誠;;唇讀研究回顧:從聾人到正常人[J];華東師范大學學報(教育科學版);2013年01期
4 梁亞玲;杜明輝;;基于DCT和ONPP的唇部特征提取[J];計算機科學;2011年05期
5 梁亞玲;杜明輝;;基于Lab色度空間a分量的唇部提取方法[J];計算機工程;2011年03期
6 何俊;張華;劉繼忠;;在DCT域進行LDA的唇讀特征提取方法[J];計算機工程與應(yīng)用;2009年32期
7 趙暉;林成龍;唐朝京;;基于視頻三音子的漢語雙模態(tài)語料庫的建立[J];中文信息學報;2009年05期
8 洪曉鵬,姚鴻勛,徐銘輝;基于句子級的唇讀語料庫及其切分算法[J];計算機工程與應(yīng)用;2005年03期
9 姚鴻勛,高文,王瑞,郎咸波;視覺語言——唇讀綜述[J];電子學報;2001年02期
10 周治,杜利民,徐彥君;漢語聽覺視覺雙模態(tài)信息的互補作用[J];中國科學E輯:技術(shù)科學;2000年03期
相關(guān)博士學位論文 前1條
1 梁亞玲;基于單視覺通道唇讀系統(tǒng)的研究[D];華南理工大學;2011年
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