Relevant bibliographies by topics / Gabor filter approach

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

Academic literature on the topic 'Gabor filter approach'

Author: Grafiati
Published: 7 June 2025
Last updated: 17 July 2025

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Journal articles on the topic "Gabor filter approach"

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Ghauri, Sajjad Ahmed, Ijaz Mansoor Qureshi, Tanveer Ahmed Cheema, and Aqdas Naveed Malik. "A Novel Modulation Classification Approach Using Gabor Filter Network." Scientific World Journal 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/643671.

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A Gabor filter network based approach is used for feature extraction and classification of digital modulated signals by adaptively tuning the parameters of Gabor filter network. Modulation classification of digitally modulated signals is done under the influence of additive white Gaussian noise (AWGN). The modulations considered for the classification purpose are PSK 2 to 64, FSK 2 to 64, and QAM 4 to 64. The Gabor filter network uses the network structure of two layers; the first layer which is input layer constitutes the adaptive feature extraction part and the second layer constitutes the s
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P, Deepan, Vidya R, Arsha Reddy M, Arul N, Ravichandran J, and Dhiravidaselvi S. "A Hybrid Gabor Filter-Convolutional Neural Networks Model for Facial Emotion Recognition System." Indian Journal of Science and Technology 17, no. 35 (2024): 3696–703. https://doi.org/10.17485/IJST/v17i35.1998.

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Abstract <strong>Objectives:</strong>&nbsp;This research aims to develop a hybrid facial emotion recognition system using integrated machine learning feature extraction techniques with convolutional neural networks model for improving the accuracy of facial emotion recognition (FER).<strong>&nbsp;Methods:</strong>&nbsp;This study introduces a novel approach that integrates various machine learning feature extraction techniques (HoG, LBP, SIFT and Gabor Filters) with Convolutional Neural Networks (CNNs). The study utilized a set of 10,500 facial emotion images of the CK+48 dataset with six diff
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Deepan, P., R. Vidya, M. Arsha Reddy, N. Arul, J. Ravichandran, and S. Dhiravidaselvi. "A Hybrid Gabor Filter-Convolutional Neural Networks Model for Facial Emotion Recognition System." Indian Journal Of Science And Technology 17, no. 35 (2024): 3696–703. http://dx.doi.org/10.17485/ijst/v17i35.1998.

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Objectives: This research aims to develop a hybrid facial emotion recognition system using integrated machine learning feature extraction techniques with convolutional neural networks model for improving the accuracy of facial emotion recognition (FER). Methods: This study introduces a novel approach that integrates various machine learning feature extraction techniques (HoG, LBP, SIFT and Gabor Filters) with Convolutional Neural Networks (CNNs). The study utilized a set of 10,500 facial emotion images of the CK+48 dataset with six different facial emotion recognition. Findings: The result fro
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Abd Almisreb, Ali, Nooritawati Md Tahir, Ahmad Farid Abidin, and Norashidah Md Din. "Speech Enhancement based on 2D Gabor Filters for Arabic Phoneme Spoken by Malay Speakers." International Journal of Engineering & Technology 7, no. 4.11 (2018): 231. http://dx.doi.org/10.14419/ijet.v7i4.11.20813.

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In this paper, a speech enhancement method using 2D Gabor filter is proposed. The proposed filter is used to enhance Arabic phoneme speech signals that have been recorded under control environment namely indoor room recording. All the phoneme signals are spoken by Malay speakers and considered as non-native Arabic speakers. Firstly, corrupted speech signals by noise must be enhanced before further processing. The effectiveness of the suggested approach is evaluated in compare with Wiener filter. It is proven that the proposed 2D Gabor filters performed appropriately for speech enhancement purp
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Abd Almisreb, Ali, Nooritawati Md Tahir, Ahmad Farid Abidin, and Norashidah Md Din. "Speech Enhancement based on 2D Gabor Filters for Arabic Phoneme Spoken by Malay Speakers." International Journal of Engineering & Technology 7, no. 4.11 (2018): 271. http://dx.doi.org/10.14419/ijet.v7i4.11.21391.

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In this paper, a speech enhancement method using 2D Gabor filter is proposed. The proposed filter is used to enhance Arabic phoneme speech signals that have been recorded under control environment namely indoor room recording. All the phoneme signals are spoken by Malay speakers and considered as non-native Arabic speakers. Firstly, corrupted speech signals by noise must be enhanced before further processing. The effectiveness of the suggested approach is evaluated in compare with Wiener filter. It is proven that the proposed 2D Gabor filters performed appropriately for speech enhancement purp
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Kusban, Muhammad, Aris Budiman, and Bambang Hari Purwoto. "Image enhancement in palmprint recognition: a novel approach for improved biometric authentication." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1299. http://dx.doi.org/10.11591/ijece.v14i2.pp1299-1307.

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Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to create the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation
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Kusban, Muhammad, Aris Budiman, and Bambang Hari Purwoto. "Image enhancement in palmprint recognition: a novel approach for improved biometric authentication." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 2 (2024): 1299–307. https://doi.org/10.11591/ijece.v14i2.pp1299-1307.

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Several researchers have used image enhancement methods to reduce detection errors and increase verification accuracy in palmprint identification. Divergent opinions exist among experts regarding the best method of image filtering to improve image palmprint recognition. Because of the unique characteristics of palmprints and the difficulties in preventing counterfeiting, image-filtering techniques are the subject of this current research. Researchers hope to create the best biometric system possible by utilizing various techniques. These techniques include image enhancement, Gabor orientation
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Wu, Hao, Xiangrong Xu, Jinbao Chu, Li Duan, and Paul Siebert. "Particle swarm optimization-based optimal real Gabor filter for surface inspection." Assembly Automation 39, no. 5 (2019): 963–72. http://dx.doi.org/10.1108/aa-04-2018-060.

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Purpose The traditional methods have difficulty to inspection various types of copper strips defects as inclusions, pits and delamination defects under uneven illumination. Therefore, this paper aims to propose an optimal real Gabor filter model for inspection; however, improper selection of Gabor parameters will cause the boundary between the defect and the background image to be not very clear. This will make the defect and the background cannot be completely separated. Design/methodology/approach The authors proposed an optimal Real Gabor filter model for inspection of copper surface defect
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Mohsen, Darvishnezhad. "Graph-Based Feature Reduction for Three-Dimensional Gabor Filter in PolSAR Image Classification." Journal of Physical Chemistry & Biophysics 11, no. 7 (2021): 01–08. https://doi.org/10.5281/zenodo.14848032.

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Polarimetric Synthetic Aperture Radar (PolSAR) image classification is one of the most important applications in remote sensing. In this paper, the goal is PolSAR image classification and also to introduce a method to obtain the best result for PolSAR image classification and recognition. In this article, we present the 3D-Gabor filters as a way in order to feature extraction of PolSAR images and get the best result with high accuracy for PolSAR image classification. Also, we prove that the 3D-Gabor filter approach can get higher accuracy than traditional methods for PolSAR images classificati
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Tadic, Vladimir, Tatjana Loncar-Turukalo, Akos Odry, et al. "A Note on Advantages of the Fuzzy Gabor Filter in Object and Text Detection." Symmetry 13, no. 4 (2021): 678. http://dx.doi.org/10.3390/sym13040678.

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This note presents a fuzzy optimization of Gabor filter-based object and text detection. The derivation of a 2D Gabor filter and the guidelines for the fuzzification of the filter parameters are described. The fuzzy Gabor filter proved to be a robust text an object detection method in low-quality input images as extensively evaluated in the problem of license plate localization. The extended set of examples confirmed that the fuzzy optimized Gabor filter with adequately fuzzified parameters detected the desired license plate texture components and highly improved the object detection when comp
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Dissertations / Theses on the topic "Gabor filter approach"

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BANSAL, KANISHKA. "A NOVEL APPROACH FOR FACE RECOGNITION USING EXTENDED BBO." Thesis, 2014. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15611.

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Face recognition has become a popular area of research in computer vision and one of the most successful applications of image analysis and understanding. We always have to extract optimal features from images to recognize an image as to achieve high accuracy as well as to be efficient. In this thesis an efficient and optimized face recognition algorithm based on Extended Species Abundance Model of Biogeography is presented. We have used Principal Component Analysis (PCA) for the face recognition technique to extract the most important features of the image as all the features, that cons
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Book chapters on the topic "Gabor filter approach"

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Sobieranski, Antonio Carlos, Rodrigo T. F. Linhares, Eros Comunello, and Aldo von Wangenheim. "A Fast Gabor Filter Approach for Multi-Channel Texture Feature Discrimination." In Advanced Information Systems Engineering. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-319-12568-8_17.

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Michels, Dominik Ludewig, and Gerrit Alexander Sobottka. "A Gabor Filter-Based Approach to Leaf Vein Extraction and Cultivar Classification." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39643-4_12.

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Avinash, S., K. Manjunath, and S. Senthil Kumar. "Modified Gabor Filter (MGF) Image Enhancement Approach for Early Detection of Lung Cancer." In Lecture Notes in Electrical Engineering. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1420-3_177.

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Patil, Vinodkumar R., and Tushar H. Jaware. "Random Forest and Gabor Filter Bank Based Segmentation Approach for Infant Brain MRI." In Advances in Intelligent Systems and Computing. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2008-9_25.

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Imran, Mohd, and Mohammad Sarosh Umar. "A Novel Authentication Approach Based on Level 2 Minutiae-based Feature Extraction Using Gabor Filter." In Innovations in Sustainable Technologies and Computing. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-1111-6_15.

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Hegde, Ganapatikrishna, M. Seetha, and Nagaratna Hegde. "Facial Expression Recognition Using Entire Gabor Filter Matching Score Level Fusion Approach Based on Subspace Methods." In Mining Intelligence and Knowledge Exploration. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26832-3_6.

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Nitish, Amit Kr Singh, and Rajesh Singla. "Different Approaches of Classification of Brain Tumor in MRI Using Gabor Filters for Feature Extraction." In Advances in Intelligent Systems and Computing. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0751-9_108.

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Pradeep, N. R., and J. Ravi. "An Revolutionary Fingerprint Authentication Approach Using Gabor Filters for Feature Extraction and Deep Learning Classification Using Convolutional Neural Networks." In Lecture Notes in Networks and Systems. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8512-5_38.

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Dash, Sonali, Priyadarsan Parida, and Gupteswar Sahu. "An Enhanced Gabor Filter Based on Heat-Diffused Top Hat Transform for Retinal Blood Vessel Segmentation." In Advances in Medical Technologies and Clinical Practice. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-6957-6.ch013.

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Precise retinal blood vessels segmentation is a vital assignment to diagnose many pathological ailments. Here, an efficient approach has been presented for the segmentation of retinal vessels that includes pre-processing, segmentation, and the post-processing stage. In the pre-processing stage, the retinal images are denoised and restored with the connected vessel lines by utilizing anisotropic diffusion filter. In the next step, retinal images are enhanced by using top hat transform. Further, Gabor filters of various orientations are applied on top hat transformed images to obtain different characteristics of the retinal images. Finally, hysteresis thresholding is applied for the segmentation. The accomplishment of the recommended methodology is inspected with other competitive combined methodologies based on median filter and Gabor filter using different performance indicators. The approach can be used effectively for diagnosis of different ocular disorders, like diabetic retinopathy and glaucoma, which can be followed by different surgical procedures for further treatment.
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"A Gabor Filter-Based Feature Points Matching Approach." In International Conference on Advanced Computer Theory and Engineering (ICACTE 2009). ASME Press, 2009. http://dx.doi.org/10.1115/1.802977.paper125.

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Conference papers on the topic "Gabor filter approach"

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Boukabou, W. R., L. Ghouti, and A. Bouridane. "Face Recognition Using a Gabor Filter Bank Approach." In First NASA/ESA Conference on Adaptive Hardware and Systems (AHS'06). IEEE, 2006. http://dx.doi.org/10.1109/ahs.2006.39.

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Thilagamani, S., and N. Shanthi. "Gaussian and Gabor Filter Approach for object segmentation." In 2013 International Conference on Optical Imaging Sensor and Security (ICOSS). IEEE, 2013. http://dx.doi.org/10.1109/icoiss.2013.6678406.

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Agarwal, Shalini, Pawan Kumar Verma, and Mohd Aamir Khan. "An optimized palm print recognition approach using Gabor filter." In 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT). IEEE, 2017. http://dx.doi.org/10.1109/icccnt.2017.8203919.

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Ardizzone, Edoardo, Roberto Pirrone, Camillo Gioe', and Orazio Gambino. "Homomorphic Approach to RF - Inhomogeneity Removal Based on Gabor Filter." In EUROCON 2007 - The International Conference on "Computer as a Tool". IEEE, 2007. http://dx.doi.org/10.1109/eurcon.2007.4400518.

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Sivakumar, R., Manu Eldho, C. V. Jiji, Anand Vinekar, and Renu John. "Computer aided screening of retinopathy of prematurity — A multiscale Gabor filter approach." In 2016 Sixth International Symposium on Embedded Computing and System Design (ISED). IEEE, 2016. http://dx.doi.org/10.1109/ised.2016.7977093.

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Silva, Angelo, and Renato Ishii. "A new time series classification approach based on recurrence quantification analysis and Gabor filter." In SAC 2016: Symposium on Applied Computing. ACM, 2016. http://dx.doi.org/10.1145/2851613.2851891.

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Tyagi, Divya, Akhilesh Verma, and Sakshi Sharma. "An improved method for facial expression recognition using hybrid approach of CLBP and Gabor filter." In 2017 International Conference on Computing, Communication and Automation (ICCCA). IEEE, 2017. http://dx.doi.org/10.1109/ccaa.2017.8229990.

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Afaq, Shajal, and Anamika Jain. "MAMMO-Net: An Approach for Classification of Breast Cancer using CNN with Gabor Filter in Mammographic Images." In 2022 International Conference on Computational Intelligence and Sustainable Engineering Solutions (CISES). IEEE, 2022. http://dx.doi.org/10.1109/cises54857.2022.9844320.

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Islam, Bayezid, Firoz Mahmud, and Arfat Hossain. "Facial Expression Region Segmentation Based Approach to Emotion Recognition Using 2D Gabor Filter and Multiclass Support Vector Machine." In 2018 21st International Conference of Computer and Information Technology (ICCIT). IEEE, 2018. http://dx.doi.org/10.1109/iccitechn.2018.8631922.

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Jagtap, Shilpa, J. L. Mudegaonkar, Sanjay Patil, and Dinesh Bhoyar. "A Novel Approach for Diagnosis of Diabetes Using Iris Image Processing Technique and Evaluation Parameters." In National Conference on Relevance of Engineering and Science for Environment and Society. AIJR Publisher, 2021. http://dx.doi.org/10.21467/proceedings.118.37.

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This paper presented here deals with study of identification and verification approach of Diabetes based on human iris pattern. In the pre-processing of this work, region of interest according to color (ROI) concept is used for iris localization, Dougman's rubber sheet model is used for normalization and Circular Hough Transform can be used for pupil and boundary detection. To extract features, Gabor Filter, Histogram of Oriented Gradients, five level decomposition of wavelet transforms likeHaar, db2, db4, bior 2.2, bior6.8 waveletscan be used. Binary coding scheme binaries’ the feature vector
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