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Journal articles on the topic 'Gabor filter approach'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

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> 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> Methods:</strong> 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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Bhatia, Neha, Himani Himani, and Chander Kant. "A Novel Approach to Address Sensor Interoperability Using Gabor Filter." Oriental journal of computer science and technology 10, no. 2 (2017): 446–53. http://dx.doi.org/10.13005/ojcst/10.02.27.

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Biometric authentication using fingerprint is one of the unique and reliable method of verification processes. Biometric System suffers a signiﬁcant loss of performance when the sensor is changed during enrollment and authentication process. In this paper fingerprint sensor interoperability problem is addressed using Gabor ﬁlter and classifying images into good and poor quality. Gabor ﬁlters play an important role in many application areas for the enhancement of various types of fingerprint images. Gabor ﬁlters can remove noise, preserve the real ridges and valley structures, and it is used fo

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Qadir, Tara Othman, Nik Shahidah Taujuddin, and Norfaiza Fuad. "A New Feature Extraction Approach in Classification for Improving the Accuracy in Iris Recognition." JOIV : International Journal on Informatics Visualization 7, no. 4 (2023): 2161. http://dx.doi.org/10.62527/joiv.7.4.1373.

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Personal identity is becoming increasingly vital to meet the increasing security standards of today's business society. Iris recognition is one of the most accurate biometric technologies currently in use. Iris recognition is employed in high-security sectors due to its dependability and flawless identification rates. The steps of iris identification, comprising image preparation, extraction of features, and classifier creation, are described thoroughly in the primary portion of this research. The feature extraction stage is the most important in an iris identification system since it extracts

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GOWDA, RAHUL, SHALIN M. MEHTA, YUE YANG, and BAOXIN LI. "ADAPTIVE NONLINEAR IMAGE ENHANCEMENT OF GAUSSIAN DEGRADED IMAGES." International Journal of Image and Graphics 10, no. 03 (2010): 365–93. http://dx.doi.org/10.1142/s0219467810003822.

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An adaptive technique for nonlinear image enhancement using Gabor filters is proposed. A set of Gabor filters are employed to extract high-pass components from the blurred image and these components are then nonlinearly processed before adding back to the input image for enhancement. Further, we propose a novel method for fast blur estimation and we establish an empirical relationship between the estimated blur and the optimal Gabor filter parameters, resulting in an enhancement system that is adaptive to the degree of blur in the input image. Extensive evaluation, including both PSNR-based ob

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Bhargava, Neeraj, Ritu Bhargava, Pramod Singh Rathore, and Abhishek Kumar. "Texture Recognition Using Gabor Filter for Extracting Feature Vectors With the Regression Mining Algorithm." International Journal of Risk and Contingency Management 9, no. 3 (2020): 31–44. http://dx.doi.org/10.4018/ijrcm.2020070103.

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This article considered only natural types of texture and then applying the Gabor filter for better classifications. The concept used is to discard the stochastic features to avoid any mixing of feature vector while it is extracting from the image dataset. The proposed approach has considered the Gabor filter for texture recognition primarily but with the combined method of spatial width and orientation to get the optimal alignment, this optical alignment mine the maximum feature vector by applying the REP algorithm over the data mined from the texture. This will result in better accuracy in t

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Jones, J. P., and L. A. Palmer. "An evaluation of the two-dimensional Gabor filter model of simple receptive fields in cat striate cortex." Journal of Neurophysiology 58, no. 6 (1987): 1233–58. http://dx.doi.org/10.1152/jn.1987.58.6.1233.

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1. Using the two-dimensional (2D) spatial and spectral response profiles described in the previous two reports, we test Daugman's generalization of Marcelja's hypothesis that simple receptive fields belong to a class of linear spatial filters analogous to those described by Gabor and referred to here as 2D Gabor filters. 2. In the space domain, we found 2D Gabor filters that fit the 2D spatial response profile of each simple cell in the least-squared error sense (with a simplex algorithm), and we show that the residual error is devoid of spatial structure and statistically indistinguishable fr

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Tang, Wei, Fangxiu Jia , and Xiaoming Wang. "Image Large Rotation and Scale Estimation Using the Gabor Filter." Electronics 11, no. 21 (2022): 3471. http://dx.doi.org/10.3390/electronics11213471.

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This paper proposes a novel image large rotation and scale estimation method based on the Gabor filter and pulse-coupled neural network (PCNN). First, the Gabor features of the template image and its rotated one are extracted by performing the Gabor filter. Second, we present a modified PCNN model to measure the similarity between the Gabor features of the image and its rotated one. Finally, the rotation angle is calculated by searching the global minimum of the correlation coefficients. Besides rotation estimation, we also propose a scale estimation method based on the max-projection strategy

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Megha, Hegde, and Sivakumar P.Agalya. "Development and Implementation of VLSI Reconfigurable Architecture for Gabor Filter in Medical Imaging Application." International Journal of Engineering and Management Research 8, no. 3 (2018): 71–76. https://doi.org/10.31033/ijemr.8.3.10.

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The Gabor filter is a very effective tool in visual search approaches and multimedia applications. This filter provides high resolution in time-frequency domains and thus finds use in object recognition, character recognition and pattern recognition applications. Medical Image analysis using image processing algorithms is one of the best ways of diagnosing diseases inside human body. The Gabor wavelets resemble the visual cortex cell operation of mammalian brains and hence are best suited for biological image analysis. A Tonsillitis detection system is proposed here using Gabor filtering appro

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Wang, Mingwei, Lang Gao, Xiaohui Huang, Ying Jiang, and Xianjun Gao. "A Texture Classification Approach Based on the Integrated Optimization for Parameters and Features of Gabor Filter via Hybrid Ant Lion Optimizer." Applied Sciences 9, no. 11 (2019): 2173. http://dx.doi.org/10.3390/app9112173.

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Texture classification is an important topic for many applications in machine vision and image analysis, and Gabor filter is considered one of the most efficient tools for analyzing texture features at multiple orientations and scales. However, the parameter settings of each filter are crucial for obtaining accurate results, and they may not be adaptable to different kinds of texture features. Moreover, there is redundant information included in the process of texture feature extraction that contributes little to the classification. In this paper, a new texture classification technique is deta

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Lahmiri, Salim, and Mounir Boukadoum. "Hybrid Discrete Wavelet Transform and Gabor Filter Banks Processing for Features Extraction from Biomedical Images." Journal of Medical Engineering 2013 (April 15, 2013): 1–13. http://dx.doi.org/10.1155/2013/104684.

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A new methodology for automatic feature extraction from biomedical images and subsequent classification is presented. The approach exploits the spatial orientation of high-frequency textural features of the processed image as determined by a two-step process. First, the two-dimensional discrete wavelet transform (DWT) is applied to obtain the HH high-frequency subband image. Then, a Gabor filter bank is applied to the latter at different frequencies and spatial orientations to obtain new Gabor-filtered image whose entropy and uniformity are computed. Finally, the obtained statistics are fed to

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Oladele Aro, Taye, Aishat Oladayo Jimoh-Mahmud, Adekunle Olugbenga Ejidokun, Ayodeji Abimbola Owonipa, and Olakunle Isaac Ifawoye. "Kernelized support vector machines for modified Gabor features facial recognition." Journal of Applied Science, Information and Computing 5, no. 2 (2024): 23–32. http://dx.doi.org/10.59568/jasic-2024-5-2-04.

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The Gabor-filter approach has been extensively used in the recognition of patterns most especially in the extraction of features during image processing. Gabor filters usefulness explored in face recognition is traceable to its computational properties and biological relevance. Despite all the distinct characteristics of Gabor filters, it suffers from high feature dimensionality. This has led majorly to computational problems in any Gabor-based facial recognition model. The paper presents modified Gabor features for face recognition by introducing a meta-heuristics optimization algorithm using

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MUNEESWARAN, K., L. GANESAN, S. ARUMUGAM, and P. HARINARAYAN. "A NOVEL APPROACH COMBINING GABOR WAVELET AND MOMENTS FOR TEXTURE SEGMENTATION." International Journal of Wavelets, Multiresolution and Information Processing 03, no. 04 (2005): 559–72. http://dx.doi.org/10.1142/s0219691305001020.

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In this work, an effective method has been proposed for texture segmentation, which incorporates the best features of filter bank and statistical approaches. This technique combines the features of Gabor wavelets (filter based) and General Moments (statistical) approaches. The method has been successfully tested for various textures from Brodatz texture collection. The relative performance of this method against the conventional approaches has been analyzed using Fisher Criterion.

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Arvind, Pratul, and Rudra Prakash Maheshwari. "A Gabor Filter Based Approach for Locating Faults in Distribution." Advanced Materials Research 403-408 (November 2011): 5007–14. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.5007.

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Electric Power Distribution System is a complex network of electrical power system. Also, large number of lines on a distribution system experiences regular faults which lead to high value of current. Speedy and precise fault location plays a pivotal role in accelerating system restoration which is a need of modern day. Unlike transmission system which involves a simple connection, distribution system has a very complicated structure thereby making it a herculean task to design the network for computational analysis. In this paper, the authors have simulated IEEE 13- node distribution system u

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AlJubayrin, Saad, Mubashar Sarfraz, Sajjad A. Ghauri, Muhammad Rizwan Amirzada, and Teweldebrhan Mezgebo Kebedew. "Artificial Bee Colony Based Gabor Parameters Optimizer (ABC-GPO) for Modulation Classification." Computational Intelligence and Neuroscience 2022 (September 30, 2022): 1–9. http://dx.doi.org/10.1155/2022/9464633.

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Modulation classification is one of the essential requirements in the various cognitive radio applications where prior information about the incoming signal is unknown. The modulation classification using a pattern recognition approach can be achieved in 2 modules: first, parameters are extracted from the noisy signal, and then feature selection is carried out using a Gabor filter network (GFN). In the second module, features are exploited for classification purposes. The modulation formats considered for the purpose of classification are BPSK, QPSK, 8PSK, 16PSK, 64PSK, 4FSK, 8FSK, 16FSK, QAM,

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Kumar, Upendra. "Significant Enhancement of Segmentation Efficiency of Retinal Images Using Texture-Based Gabor Filter Approach Followed by Optimization Algorithm." International Journal of Computer Vision and Image Processing 7, no. 1 (2017): 44–58. http://dx.doi.org/10.4018/ijcvip.2017010103.

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Considering Retinal image as textured image, its texture based segmentation is required to identify the presence of retinal diseases. This pre-processing is important in automatic detection system for recognizing the abnormality present in the retinal images. Likewise, the proposed system mainly focused on diabetic retinopathy disease caused into eye –retina, generally leads to eye-blindness. Inspired from robust human's texture based segmentation capability, a mathematical model of the eye was formulated. A texture based Gabor filter was applied to get the output feature helping in detecting

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Kumar, Anubhav. "An Efficient Approach for Text Extraction in Images and Video Frames Using Gabor Filter." International Journal of Computer and Electrical Engineering 6, no. 4 (2014): 316–20. http://dx.doi.org/10.7763/ijcee.2014.v6.845.

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Feng Zhu, Xian-Da Zhang, and Ya-Feng Hu. "Gabor Filter Approach to Joint Feature Extraction and Target Recognition." IEEE Transactions on Aerospace and Electronic Systems 45, no. 1 (2009): 17–30. http://dx.doi.org/10.1109/taes.2009.4805260.

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Yahya, Ismail Ibrahim, and Abdul-Jabbar Sultan Enaam. "Iris recognition based on 2D Gabor filter." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 325–34. https://doi.org/10.11591/ijece.v13i1.pp325-334.

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Iris recognition is a type of biometrics technology that is based on physiological features of the human body. The objective of this research is to recognize and identify iris among many irises that are stored in a visual database. This study employed a left and right iris biometric framework for inclusion decision processing by combining image processing and artificial bee colony. The proposed approach was evaluated on a visual database of 280 colored iris pictures. The database was then divided into 28 clusters. Images were preprocessed and texture features were extracted based Gabor filters

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MISS., SNEHA S. MANE, and K. R. DESAI DR. "FACIAL FEATURE EXTRACTION USING LBP WITH GABOR FILTER." IJIERT - International Journal of Innovations in Engineering Research and Technology 4, no. 4 (2017): 40–45. https://doi.org/10.5281/zenodo.1461211.

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<strong>A Facial Feature Extraction approach is proposed here using LBP. The system first pre-processes the input image for illumination changes and noise invariance with the help of Adaptive Histogram Equalization. Then Face detection is proposed and Gabor filter is also applied to produce magnitude pictures. Finally,the proposed LBP is used to extract features of the facial image.</strong> <strong>https://www.ijiert.org/paper-details?paper_id=141054</strong>

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Ibrahim, Yahya Ismail, and Enaam Abdul-Jabbar Sultan. "Iris recognition based on 2D Gabor filter." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 1 (2023): 325. http://dx.doi.org/10.11591/ijece.v13i1.pp325-334.

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<span lang="EN-US">Iris recognition is a type of biometrics technology that is based on physiological features of the human body. The objective of this research is to recognize and identify iris among many irises that are stored in a visual database. This study employed a left and right iris biometric framework for inclusion decision processing by combining image processing and artificial bee colony. The proposed approach was evaluated on a visual database of 280 colored iris pictures. The database was then divided into 28 clusters. Images were preprocessed and texture features were extr

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Nikolov, Dimitar Nikolov, and Diana Dimitrova Tsankova. "Features Extraction for Pollen Recognition Using Gabor Filters." Food Science and Applied Biotechnology 1, no. 2 (2018): 86. http://dx.doi.org/10.30721/fsab2018.v1.i2.11.

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The aim of the article is to investigate the features extraction from microscope images of pollens for a classification of honey on the base of its botanical origin. A filter-bank of Gabor filters (as a biologically inspired recognition system) is used to obtain features, which are then post-processed using normalization, down-sampling (by bicubic interpolation), and principal components analysis (PCA). PCA is used for reducing the features size and a proper visualization of the features extraction results. Microscope images from the European pollen database, including pollen images of linden,

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Karan Kumar, Deepanshu Gupta, Shaurya Nayyar, Ashish Gupta, and Jyotsna Singh. "Multi-channel and multi-featured extended orb with gabor filter and non-maximum suppression." World Journal of Advanced Engineering Technology and Sciences 12, no. 1 (2024): 102–8. http://dx.doi.org/10.30574/wjaets.2024.12.1.0183.

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This research paper presents an enhanced approach to feature extraction using the Oriented FAST and Rotated BRIEF (ORB) algorithm (Rublee et al., 2014). The proposed method leverages the power of Gabor filters (Mehrotra et al., 1992) in combination with Non-Maximum Suppression (Neuback and Van Gool, 2006) to improve the robustness and efficiency of feature detection in computer vision applications. The process begins with the acquisition of an RGB image, which is then transformed into seven single-channel images representing different color and intensity aspects: red, green, blue, hue, saturat

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Gao, Xiaojing, Heru Xue, Xin Pan, Xinhua Jiang, Yanqing Zhou, and Xiaoling Luo. "Somatic Cells Recognition by Application of Gabor Feature-Based (2D)2PCA." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 12 (2017): 1757009. http://dx.doi.org/10.1142/s0218001417570099.

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In this paper, we propose a novel approach of Gabor feature based on bi-directional two-dimensional principal component analysis ((2D)2PCA) for somatic cells recognition. Firstly, Gabor features of different orientations and scales are extracted by the convolution of Gabor filter bank. Secondly, dimensionality reduction of the feature space applies (2D)2PCA in both row and column. Finally, the classifier uses Support Vector Machine (SVM) to achieve our goal. The experimental results are obtained using a large set of images from different sources. The results of our proposed method are not only

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Li, Xi, Zhangyong Li, Dewei Yang, Lisha Zhong, Lian Huang, and Jinzhao Lin. "Research on Finger Vein Image Segmentation and Blood Sampling Point Location in Automatic Blood Collection." Sensors 21, no. 1 (2020): 132. http://dx.doi.org/10.3390/s21010132.

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In the fingertip blood automatic sampling process, when the blood sampling point in the fingertip venous area, it will greatly increase the amount of bleeding without being squeezed. In order to accurately locate the blood sampling point in the venous area, we propose a new finger vein image segmentation approach basing on Gabor transform and Gaussian mixed model (GMM). Firstly, Gabor filter parameter can be set adaptively according to the differential excitation of image and we use the local binary pattern (LBP) to fuse the same-scale and multi-orientation Gabor features of the image. Then, f

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Bennet, M. Anto, G. Sankar Babu, S. Mekala, S. Natarjan, and N. Srinivasan. "Performance and Analysis of Automatic Detection Of Ground-Glass Pattern in Lung Disease using High-Resolution Computed Tomography." International Journal of Advances in Applied Sciences 4, no. 3 (2015): 95. http://dx.doi.org/10.11591/ijaas.v4.i3.pp95-102.

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This study proposes an approach for automatic detection of Ground glass pattern, a lung disease, from Computed Tomography (CT) and High Resolution Computed Tomography (HRCT) scans of the lung. The algorithm is based on frequency spectrum analysis of image using Gabor filter bank. Gabor filter banks are used to support the frequency extraction process. These algorithms when applied to HRCT images will assist doctors to gain more information than from the CT images. The tasks are completed in three steps: Preliminary mask formation, Peripheral mask formation and finally post processing. By these

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ZHANG, WEIPENG, YUAN YAN TANG, and XINGE YOU. "FINGERPRINT ENHANCEMENT USING WAVELET TRANSFORM COMBINED WITH GABOR FILTER." International Journal of Pattern Recognition and Artificial Intelligence 18, no. 08 (2004): 1391–406. http://dx.doi.org/10.1142/s0218001404003861.

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The performance of automatic fingerprint identification system (AFIS) is heavily determined by the quality of the input image, thus an effective method to enhance the fingerprint image is essential in such a system. In this paper, we combine the filter-based method, which is mostly used nowadays with wavelet transform to achieve a more reliable and effective approach to fingerprint enhancement. This novel approach consists of five main steps, namely: (1) normalization, (2) decomposition, (3) wavelet coefficient adjustment, (4) Gabor filtering, and (5) reconstruction. Using this new method, a m

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Gonzaga de O, S. L., F. Viola, and A. Conci. "An approach for enhancing fingerprint images using adaptive Gabor filter parameters." Pattern Recognition and Image Analysis 18, no. 3 (2008): 497–506. http://dx.doi.org/10.1134/s105466180803019x.

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Tamilselvi, S. "A Novel Based Approach for iris code Recognization Using Gabor Filter." IOSR Journal of Electronics and Communication Engineering 4, no. 5 (2013): 32–37. http://dx.doi.org/10.9790/2834-0453237.

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Dora, Lingraj, Sanjay Agrawal, Rutuparna Panda, and Ajith Abraham. "An evolutionary single Gabor kernel based filter approach to face recognition." Engineering Applications of Artificial Intelligence 62 (June 2017): 286–301. http://dx.doi.org/10.1016/j.engappai.2017.04.011.

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Ullah, Sajeed, Mehran Ahmad, Shahzad Anwar, and Muhammad Irfan Khattak. "An Intelligent Hybrid Approach for Brain Tumor Detection." Pakistan Journal of Engineering and Technology 6, no. 1 (2023): 42–50. http://dx.doi.org/10.51846/vol6iss1pp34-42.

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Brain tumours are quickly increasing in prevalence all over the world. It causes the deaths of thousands of individuals annually. Misdiagnosis of brain tumours often results in unnecessary treatment, further lowering the survival rate of the affected individuals. Prompt medical diagnosis is crucial to improve the prognosis for patients with brain tumours. Positive advancements in deep and machine learning domains have been made due to repeated achievements in supporting medical practitioners in making correct diagnoses utilizing computer-aided diagnostic tools. Deep convolutional layers are su

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Sohn, Woonbae, Taekyung Kim, Cheon Woo Moon, et al. "Unsupervised Learning for the Automatic Counting of Grains in Nanocrystals and Image Segmentation at the Atomic Resolution." Nanomaterials 14, no. 20 (2024): 1614. http://dx.doi.org/10.3390/nano14201614.

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Identifying the grain distribution and grain boundaries of nanoparticles is important for predicting their properties. Experimental methods for identifying the crystallographic distribution, such as precession electron diffraction, are limited by their probe size. In this study, we developed an unsupervised learning method by applying a Gabor filter to HAADF-STEM images at the atomic level for image segmentation and automatic counting of grains in polycrystalline nanoparticles. The methodology comprises a Gabor filter for feature extraction, non-negative matrix factorization for dimension redu

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Ghauri, Sajjad Ahmed, and Ijaz Mansoor Qureshi. "M-PAM Signals Classification Using Modified Gabor Filter Network." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/262180.

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A Modified Gabor Filter (MGF) network based approach is used for feature extraction and classification ofM-ary Pulse Amplitude Modulated (M-PAM) signals by adaptively tuning the parameters of MGF network. Modulation classification ofM-PAM signals is done under the influence of additive white Gaussian noise (AWGN) and channel effects such as Rayleigh flat fading and Rician flat fading. The MGF network uses the network structure of two layers. First layer which is input layer constitutes the adaptive feature extraction part and second layer constitutes the signal classification part. The Gabor a

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Khalil, Mohammed Sayim. "Deducting Abnormalities in Chest X-Rays using Gabor Filters and Deep Neural Network (DNN)." Jurnal Kejuruteraan 36, no. 5 (2024): 1965–72. http://dx.doi.org/10.17576/jkukm-2024-36(5)-16.

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Chest X-rays are widely used as a diagnostic tool to detect respiratory diseases. The complexity of the texture and structures shown in the resulting images can make their interpretation difficult. A more accurate interpretation would help diagnose respiratory diseases earlier, resulting in more effective and timely treatment. In this research, the author proposes a new method for detecting abnormalities in chest X-ray images using Gabor filters and artificial intelligence (AI). Gabor filters are a type of filter that can be used to extract texture features from images. These features can then

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Alaei, Niloofar, Amin Roshandel Kahoo, Abolghasem Kamkar Rouhani, and Mehrdad Soleimani. "Seismic resolution enhancement using scale transform in the time-frequency domain." GEOPHYSICS 83, no. 6 (2018): V305—V314. http://dx.doi.org/10.1190/geo2017-0248.1.

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Reducing uncertainty in geologic interpretation of petroleum reservoir containing thin layers requires increasing vertical resolution via appropriate advanced resolution enhancement methods. This problem was resolved here by introducing an alternative approach in resolution enhancement. Our method uses Gabor deconvolution (GD) combined with wavelet scaling. First, the seismic trace is transformed in the time-frequency domain using the Gabor transform. Subsequently, the Gabor magnitude spectrum of the seismic trace is smoothed to estimate the wavelet magnitude, which is then divided by the orig

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Fouad, Amal. "MRI Brain Cancer Diagnosis Approach Using Gabor Filter and Support Vector Machine." International Journal of Emerging Trends in Engineering Research 7, no. 12 (2019): 907–14. http://dx.doi.org/10.30534/ijeter/2019/297122019.

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Nandeesh, M. D., and M. Meenakshi. "Detection of Tumor Using Gabor Filter for Multimodal Images." Journal of Computational and Theoretical Nanoscience 17, no. 9 (2020): 4325–30. http://dx.doi.org/10.1166/jctn.2020.9070.

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Imaging segmentation techniques play a significant factor in medical justification for diagnosis and therapy application in healthcare industries. These noninvasive procedures assist the physician to visualize the vital part of the human body planned for treatment. Multimodal fused images from Computer tomography (CT) and Magnetic resonance imaging (MRI) provides prominent results in detection of the tumor. Maximum information about the image cannot be obtained from individual technique to assess the location and its dimension of tumor. A fusion of multimodal images like MRI and CT images are

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Rimiru, Richard M., Judy Gateri, and Micheal W. Kimwele. "GaborNet: investigating the importance of color space, scale and orientation for image classification." PeerJ Computer Science 8 (February 25, 2022): e890. http://dx.doi.org/10.7717/peerj-cs.890.

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Content-Based Image Retrieval (CBIR) is the cornerstone of today’s image retrieval systems. The most distinctive retrieval approach used, involves the submission of an image-based query whereby the system is used in the extraction of visual characteristics like the shape, color, and texture from the images. Examination of the characteristics is done for ensuring the searching and retrieval of proportional images from the image database. Majority of the datasets utilized for retrieval lean towards to comprise colored images. The colored images are regarded as in RGB (Red, Green, Blue) form. Mos

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Sharma, Manish, Vikash Shrivastava, and Vivek Shrivastava. "Development of content based image retrieval system using wavelet and Gabor transform." COMPUSOFT: An International Journal of Advanced Computer Technology 02, no. 06 (2013): 147–51. https://doi.org/10.5281/zenodo.14602865.

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A novel approach to image retrieval using color, texture and spatial information is proposed. The color information of an image is represented by the proposed color hologram, which takes into account both the occurrence of colors of pixels and the colors of their neighboring pixels. The proposed Fuzzy Color homogeneity, encoded by fuzzy sets, is incorporated in the color hologram computation. The texture information is described by the mean, variance and energy of wavelet decomposition coefficients in all sub bands. The spatial information is characterized by the class parameters obtained auto

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Yavuz, Zafer, and Cemal Köse. "Blood Vessel Extraction in Color Retinal Fundus Images with Enhancement Filtering and Unsupervised Classification." Journal of Healthcare Engineering 2017 (2017): 1–12. http://dx.doi.org/10.1155/2017/4897258.

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Retinal blood vessels have a significant role in the diagnosis and treatment of various retinal diseases such as diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. For this reason, retinal vasculature extraction is important in order to help specialists for the diagnosis and treatment of systematic diseases. In this paper, a novel approach is developed to extract retinal blood vessel network. Our method comprises four stages: (1) preprocessing stage in order to prepare dataset for segmentation; (2) an enhancement procedure including Gabor, Frangi, and Gauss filters obtained se

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Chalie, Minalu, and Zewdie Mossie. "Pulmonary Disease Identification and Classification Using Deep Learning Approach." Ethiopian International Journal of Engineering and Technology 1, no. 2 (2023): 50–65. http://dx.doi.org/10.59122/144cfc16.

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Deep Learning (DL) based model has shown great performance in the medical field for the detection of diseases. We examine the difficulty of classifying pulmonary disease (PD) classification in X-ray images in order to address medical-related issues. PD is a disease that prevents the lungs from functioning properly. Various researches have been done to automate the detection of pulmonary diseases. However, most studies concentrate only on identifying the presence or absence of the disease. As well, almost all studies ignore the automatic classification of tuberculosis in the lungs with other di

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J.venkatesh, J. venkatesh. "A Study and Analysis of Gabor Filter and K-Nearest Neighbor Approach on Minutia Matching for Fingerprint Recognition." Indian Journal of Applied Research 3, no. 9 (2011): 204–5. http://dx.doi.org/10.15373/2249555x/sept2013/64.

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