Relevant bibliographies by topics / Log-Gabor wavelet

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Log-Gabor wavelet'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Log-Gabor wavelet"

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LI, Ning, and De XU. "2D Log-Gabor Wavelet Based Action Recognition." IEICE Transactions on Information and Systems E92-D, no. 11 (2009): 2275–78. http://dx.doi.org/10.1587/transinf.e92.d.2275.

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Li, Ji-liang, Xiang-zhong Fang, and Jun Hou. "Mean shift based log-Gabor wavelet image coding." Journal of Zhejiang University-SCIENCE A 8, no. 4 (April 2007): 620–24. http://dx.doi.org/10.1631/jzus.2007.a0620.

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Agarwal, Megha, and Rudra Prakash Maheshwari. "Content Based Image Retrieval Based on Log Gabor Wavelet Transform." Advanced Materials Research 403-408 (November 2011): 871–78. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.871.

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This paper proposes a novel approach of content based image retrieval based on Log Gabor Wavelet Transform (LGWT). It is observed that LGWT better represents an image compared to Gabor Wavelet Transform (GWT). Experimental results illustrate the comparative analysis of proposed retrieval system and the retrieval system based on GWT feature descriptor. It is verified that LGWT based retrieval system improves the average precision and average recall (55.46% and 32.03% respectively) from GWT based retrieval system (50.61% and 31.63% respectively). All the experiments are performed on Corel 1000 natural image database.
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Li, Qi, Peng Ge, Hua Jun Feng, and Zhi Hai Xu. "Image Displacement Detection under Low Illumination Using Joint Transform Correlator with Wavelet Denoising." Applied Mechanics and Materials 128-129 (October 2011): 602–6. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.602.

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Since joint transform correlator (JTC) cannot directly detect the displacement between reference and target images without adequate exposure, an image displacement detection method using JTC based on log-Gabor wavelet denoising is proposed. The method uses a log-Gabor wavelet transform to denoise the reference and the target image obtained in the condition lack of enough exposure, preserving the phase information of them. Results show that the method can successfully accomplish the motion detection, RMSE of displacement measurement using JTC with wavelet denoising could be within 0.3 pixels under 1/80 of normal exposure. The method improved the detection ability of JTC in the condition of low illumination and low contrast, and has great application prospect under these circumstances.
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ZHOU, Zhi-ping, and Hui-jun WU. "Iris recognition algorithm combining wavelet transform and Log-Gabor filter." Journal of Computer Applications 29, no. 8 (October 9, 2009): 2095–97. http://dx.doi.org/10.3724/sp.j.1087.2009.02095.

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Senapati, Suman, Neeraj Bhende, and Goutam Saha. "Bayesian marginal statistics for speech enhancement using log Gabor wavelet." International Journal of Speech Technology 14, no. 3 (July 12, 2011): 193–210. http://dx.doi.org/10.1007/s10772-011-9096-2.

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Yang, Yong, Song Tong, Shuying Huang, and Pan Lin. "Log-Gabor Energy Based Multimodal Medical Image Fusion in NSCT Domain." Computational and Mathematical Methods in Medicine 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/835481.

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Multimodal medical image fusion is a powerful tool in clinical applications such as noninvasive diagnosis, image-guided radiotherapy, and treatment planning. In this paper, a novel nonsubsampled Contourlet transform (NSCT) based method for multimodal medical image fusion is presented, which is approximately shift invariant and can effectively suppress the pseudo-Gibbs phenomena. The source medical images are initially transformed by NSCT followed by fusing low- and high-frequency components. The phase congruency that can provide a contrast and brightness-invariant representation is applied to fuse low-frequency coefficients, whereas the Log-Gabor energy that can efficiently determine the frequency coefficients from the clear and detail parts is employed to fuse the high-frequency coefficients. The proposed fusion method has been compared with the discrete wavelet transform (DWT), the fast discrete curvelet transform (FDCT), and the dual tree complex wavelet transform (DTCWT) based image fusion methods and other NSCT-based methods. Visually and quantitatively experimental results indicate that the proposed fusion method can obtain more effective and accurate fusion results of multimodal medical images than other algorithms. Further, the applicability of the proposed method has been testified by carrying out a clinical example on a woman affected with recurrent tumor images.
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Senapati, Suman, Sandipan Chakroborty, and Goutam Saha. "Speech enhancement by joint statistical characterization in the Log Gabor Wavelet domain." Speech Communication 50, no. 6 (June 2008): 504–18. http://dx.doi.org/10.1016/j.specom.2008.03.004.

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Hsieh, Ching Tang, Chia Shing Hu, and Chun Wei Pan. "Automatic Facial Aging/Rejuvenating Synthesis Method." Applied Mechanics and Materials 284-287 (January 2013): 3035–39. http://dx.doi.org/10.4028/www.scientific.net/amm.284-287.3035.

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At present, the synthesizing faces of different ages does not emphasize on feature alignment and rectification of twisted images. If these situations do happen, they might cause failure and inaccuracy on synthesizing images. In this paper, we propose a reversible human facial aging/rejuvenating synthesis system which is implemented by Active Shape Model (ASM) integrated with Log-Gabor Wavelet, which can be used to search for the dementia elderly. First, we use AdaBoost and ASM algorithm to extract the feature set of human face, and rectify them by the concept of facial geometric invariance. The invariant concepts are the distance between inner corners of both eyes and the distance between the nose and chin. Then, we find manually one target image which is similar to the test image from the database, and analyze age texture of this human image by Log-Gabor wavelet in order to retrieve decomposition maps. Finally, we can effectively simulate human facial images of people of different ages by controlling the number of decomposition map of images and objectively judge the results via the density of wrinkles.
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Farouk, R. M., Mohammed Elsayed, and Mohammed Aly. "Medical Image Denoising based on Log-Gabor Wavelet Dictionary and K-SVD Algorithm." International Journal of Computer Applications 141, no. 1 (May 17, 2016): 27–32. http://dx.doi.org/10.5120/ijca2016909209.

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Dissertations / Theses on the topic "Log-Gabor wavelet"

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Naouai, Mohamed. "Localisation et reconstruction du réseau routier par vectorisation d'image THR et approximation des contraintes de type "NURBS"." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-00994333.

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Ce travail de thèse vise à mettre en place un système d'extraction de réseau routier en milieu urbain à partir d'image satellite à très haute résolution. Dans ce contexte, nous avons proposé deux méthodes de localisation de routes. La première approche est fondée sur la procédure de conversion de l'image vers un format vectoriel. L'originalité de cette approche réside dans l'utilisation d'une méthode géométrique pour assurer le passage vers une représentation vectorielle de l'image d'origine et la mise en place d'un formalisme logique fondé sur un ensemble de critères perceptifs permettant le filtrage de l'information inutile et l'extraction des structures linéaires. Dans la deuxième approche, nous avons proposé un algorithme fondé sur la théorie des ondelettes, il met particulièrement en évidence les deux volets multi-résolution et multi-direction. Nous proposons donc une approche de localisation des routes mettant en jeux l'information fréquentielle multi directionnelle issue de la transformée en ondelette Log-Gabor. Dans l'étape de localisation, nous avons présenté deux détecteurs de routes qui exploitent l'information radiométrique, géométrique et fréquentielle. Cependant, ces informations ne permettent pas un résultat exact et précis. Pour remédier à ce problème, un algorithme de suivi s'avère nécessaire. Nous proposons la reconstruction de réseaux routiers par des courbes NURBS. Cette approche est basée sur un ensemble de points de repères identifiés dans la phase de localisation. Elle propose un nouveau concept, que nous avons désigné par NURBSC, basé sur les contraintes géométriques des formes à approximer. Nous connectons les segments de route identifiés afin d'obtenir des tracés continus propres aux routes.
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Cook, James Allen. "A decompositional investigation of 3D face recognition." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16653/.

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Automated Face Recognition is the process of determining a subject's identity from digital imagery of their face without user intervention. The term in fact encompasses two distinct tasks; Face Verficiation is the process of verifying a subject's claimed identity while Face Identification involves selecting the most likely identity from a database of subjects. This dissertation focuses on the task of Face Verification, which has a myriad of applications in security ranging from border control to personal banking. Recently the use of 3D facial imagery has found favour in the research community due to its inherent robustness to the pose and illumination variations which plague the 2D modality. The field of 3D face recognition is, however, yet to fully mature and there remain many unanswered research questions particular to the modality. The relative expense and specialty of 3D acquisition devices also means that the availability of databases of 3D face imagery lags significantly behind that of standard 2D face images. Human recognition of faces is rooted in an inherently 2D visual system and much is known regarding the use of 2D image information in the recognition of individuals. The corresponding knowledge of how discriminative information is distributed in the 3D modality is much less well defined. This dissertations addresses these issues through the use of decompositional techniques. Decomposition alleviates the problems associated with dimensionality explosion and the Small Sample Size (SSS) problem and spatial decomposition is a technique which has been widely used in face recognition. The application of decomposition in the frequency domain, however, has not received the same attention in the literature. The use of decomposition techniques allows a map ping of the regions (both spatial and frequency) which contain the discriminative information that enables recognition. In this dissertation these techniques are covered in significant detail, both in terms of practical issues in the respective domains and in terms of the underlying distributions which they expose. Significant discussion is given to the manner in which the inherent information of the human face is manifested in the 2D and 3D domains and how these two modalities inter-relate. This investigation is extended to cover also the manner in which the decomposition techniques presented can be recombined into a single decision. Two new methods for learning the weighting functions for both the sum and product rules are presented and extensive testing against established methods is presented. Knowledge acquired from these examinations is then used to create a combined technique termed Log-Gabor Templates. The proposed technique utilises both the spatial and frequency domains to extract superior performance to either in isolation. Experimentation demonstrates that the spatial and frequency domain decompositions are complimentary and can combined to give improved performance and robustness.
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Haneberg-Diggs, Dominique Miguel. "Seismic attributes of the Clinton interval reservoir in the Dominion East Ohio Gabor gas storage field near North Canton, Ohio." Wright State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=wright1418759184.

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Lee, Yu-Cheng, and 李祐丞. "Facial Image Aging Synthesis Based on Log-Gabor Wavelet." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/18385318855872841410.

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碩士
淡江大學
電機工程學系碩士班
97
At present, there are many application of facial image synthesis by computer graphics such as visual entertainment, movie production, game, cosmetic examinations, and searches for missing persons, etc. For these reason, manipulation of different age on human face become a common problem and the most popular one nowadays. In this paper, we propose an approach for manipulating different age texture on human face base on face detection, and Log-Gabor wavelet. First of all, Adaboost algorithm is used to get the main facial features and to normalize them into the same size and same features position of each picture. Second, we find an appropriate target age image which is similar to subject’s image, and then we employ the properties of multi-resolution and multi-channel to extract the decomposition maps of age texture with different age on human face by using Log-Gabor wavelet. Finally, we can effectively manipulate the different age of human face through controlling the amount of decomposition map of target age images to cover on the subject’s faces image. Experimental results show that the aging synthesis of facial images can be generated well by using our proposed approach.
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Pan, Chun-Wei, and 潘俊瑋. "The Facial Image Aging Synthesis System integrated ASM with Log-Gabor Wavelet." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/73616121641260640878.

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Abstract:
碩士
淡江大學
電機工程學系碩士班
98
In present years, applications of facial image synthesis become much popular, such as visual entertainment, animations, games, cosmetic examinations, searching for missing people, etc. And our research is about missing people searching. In this thesis, we propose a human face aging synthesis system which implements by ASM integrated with Log-Gabor Wavelet. First, we use the ASM algorithm to extract the feature set of human face, and normalize them by geometric properties. Then, we find out one target image which is similar to the test image from the data base(?). And take the human image to analysis age texture by Log-Gabor wavelet, we can get the decomposition maps of age texture with different age on human face. Finally, we can effectively manipulate different human face images which are different age by controlling the amount of decomposition map of target age images which cover on the test image. From the experimental results, it seems that we can get a better performance in facial synthesis.
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Book chapters on the topic "Log-Gabor wavelet"

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Ali, Lasker Ershad, Junfeng Luo, and Jinwen Ma. "Effective Iris Recognition for Distant Images Using Log-Gabor Wavelet Based Contourlet Transform Features." In Intelligent Computing Theories and Application, 293–303. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63309-1_27.

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Conference papers on the topic "Log-Gabor wavelet"

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Biswas, Suvagata, Yonghui Wang, and Suxia Cui. "Surgically altered face detection using log-Gabor wavelet." In 2015 12th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP). IEEE, 2015. http://dx.doi.org/10.1109/iccwamtip.2015.7493965.

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XIAO, ZHITAO, ZHENGXIN HOU, and YINGCHUN GUO. "LOG GABOR WAVELET — CONSISTENT WITH HUMAN VISUAL SYSTEM CHARACTERISTICS." In Proceedings of the International Computer Congress 2004. World Scientific Publishing Company, 2004. http://dx.doi.org/10.1142/9789812702654_0006.

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Senapati, S., S. Chakroborty, and G. Saha. "Log Gabor Wavelet and Maximum a Posteriori Estimator in Speaker Identification." In 2006 Annual IEEE India Conference. IEEE, 2006. http://dx.doi.org/10.1109/indcon.2006.302757.

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Pozdin, Vladimir A., and Yingzi Du. "Performance analysis and parameter optimization for iris recognition using Log-Gabor wavelet." In Electronic Imaging 2007, edited by J. Angelo Beraldin, Fabio Remondino, and Mark R. Shortis. SPIE, 2007. http://dx.doi.org/10.1117/12.702562.

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Gao, Xinting, Farook Sattar, and Ronda Venkateswarlu. "Multiscale Corner Detection of Gray Level Images Based on Log-Gabor Wavelet Transform." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366142.

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Jian-Ming Zhang, Li-Jing Fan, Yong-Zhao Zhan, and Ping Sheng. "Reconstruction of Human Face for Different Age Based on the Log-gabor Wavelet." In 2008 International Symposium on Information Science and Engineering (ISISE). IEEE, 2008. http://dx.doi.org/10.1109/isise.2008.147.

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Arulmozhi, N., N. Manoharan, B. Sheela Rani, B. Venkatraman, and Baldev Raj. "Isolation of Defects in Radiographic Weld Images with Wavelet Denoising Using Log-Gabor Filter." In International Conference on Computational Intelligence and Multimedia Applications (ICCIMA 2007). IEEE, 2007. http://dx.doi.org/10.1109/iccima.2007.384.

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Zhengjian Ding and Yulu Du. "Fusion of Log-Gabor wavelet and orthogonal locality sensitive discriminant analysis for face recognition." In 2011 International Conference on Image Analysis and Signal Processing (IASP). IEEE, 2011. http://dx.doi.org/10.1109/iasp.2011.6109024.

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Tajouri, Imen, Ahmed Ghorbel, Walid Aydi, and Nouri Masmoudi. "An efficient iris texture analysis based on HAAR wavelet 2D Log Gabor and monogenic filter." In 2016 17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA). IEEE, 2016. http://dx.doi.org/10.1109/sta.2016.7952108.

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Kumar, Ajay, and David Zhang. "Ear authentication using Log-Gabor wavelets." In Defense and Security Symposium, edited by Salil Prabhakar and Arun A. Ross. SPIE, 2007. http://dx.doi.org/10.1117/12.720244.

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