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Coronary Angiography Print: An Automated Accurate Hidden Biometric Method Based on Filtered Local Binary Pattern Using Coronary Angiography Images

Mehmet Ali Kobat, Turker Tuncer
2021 Journal of Personalized Medicine  
The generated features are fed to neighborhood component analysis and the selected features are classified using k nearest neighbor classifier.  ...  Moreover, we discover a new hidden biometric feature using coronary angiography images and name of this hidden biometric is coronary angiography print.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jpm11101000 pmid:34683139 pmcid:PMC8538583 fatcat:hnpmcisvajgodki6adpbvm2mn4

Using Hybrid Filter-Wrapper Feature Selection with Multi-Objective Improved-Salp Optimization for Crack Severity Recognition

Esraa Elhariri, Nashwa El-Bendary, Shereen A. Taie
2020 IEEE Access  
It is noticed that using VGG16 learned features outperforms using the fused hand-crafted features by 17.7%, 15.9%, and 23.5% for fine, moderate, and severe crack recognition, respectively.  ...  The obtained experimental results show that the proposed system enhances the performance of crack severity recognition with ≈ 37% and ≈ 31% increase in recognition average accuracy and F-measure, respectively  ...  Evaluating the proposed method on the collected EEG signals using Naive Bayesian Classifier (NBC), KNN, LDA, and combinations of these classifiers proved that KNN obtained the best Kappa values on the  ... 
doi:10.1109/access.2020.2991968 fatcat:mtgr7mlejfaejadozwvqdt3irq

Classification and Analysis of Android Malware Images Using Feature Fusion Technique

Jaiteg Singh, Deepak Thakur, Tanya Gera, Babar Shah, Tamer Abuhmed, Farman Ali
2021 IEEE Access  
ACKNOWLEDGMENT Jaiteg Singh and Farman Ali contributed equally and are co-first authors.  ...  When features were extracted using LBP texture descriptors and classified using RF, it provided better classification results than LBP-SVM and LBP-KNN.  ...  Performance metrics obtained using Feature Fusion-SVM classifier achieved the highest accuracy of 93.24% using CR+AM malware images.  ... 
doi:10.1109/access.2021.3090998 fatcat:2rwq6muatnahddw6wgbjsutkxi

Coral Reef Image Classification Employing Deep Features and A Novel Local Inter Cross Weber Magnitude (LICWM) Pattern

C.Padma Priya
2021 Turkish Journal of Computer and Mathematics Education  
The traditional methods used K-Nearest Neighbor (KNN) and Random Forest (RF) for classifying deep features. The performance of the proposed method is estimated using F-score.  ...  Hence, it can assist marine experts to classify endangered and susceptible coral reefs. But, classifying coral reef images is a promising task due to its varying color, texture, shape and morphology.  ...  KNN classifier is used for classification[23] with Euclidean distance as the distance metric is given in Eq. (5). . 4. 2 2 Performance MetricsPerformance metrics are used to estimate the classification  ... 
doi:10.17762/turcomat.v12i6.1397 fatcat:hyu3uehqqfdh7ibqt2srrfyvcq

Breast Cancer Classification using Local Directional Ternary Patterns

Mary Mwadulo, Stephen Mutua, Raphael Angulu
2020 International Journal of Computer Applications  
Findings from empirical records for the MIAS breast cancer dataset and using different classifiers show that LDTP attains a higher accuracy level for both normal/abnormal and benign/malignant classification  ...  in a dataset, and the Local Directional Patterns (LDP) use orientation responses to derive an image gradient disregarding the central pixel and 8−k responses.  ...  Stephen Mutua and Dr. Raphael Angulu for their unlimited guidance and consistent counsel during the entire research.  ... 
doi:10.5120/ijca2020920449 fatcat:nzpihqutrregpmdpxdz2727nam

Texture analysis of lace images using histogram and local binary patterns under rotation variation

Wael Ben Soltana, Alice Porebski, Nicolas Vandenbroucke, Adeel Ahmad, Denis Hamad
2014 International Image Processing, Applications and Systems Conference  
We further evaluate two variants of LBP; primarily the LBP Histogram (LBPB) and secondly the Fourier Transform applied on the LBP Histogram (LBPFFT).  ...  The classification rate evaluates the discrimination degree of each descriptor via the k nearest neighbors kNN classifier.  ...  ). kNN classifier is applied for all types of features with k=1.  ... 
doi:10.1109/ipas.2014.7043325 fatcat:l6xoldrfqjainapw3cni53oupy

Multi-Classifiers Face Recognition System Using LBPP Face Representation

Abdellatif Dahmouni, Nabil Aharrane, Karim El Moutaouakil, Khalid Satori
2017 International Journal of Innovative Computing, Information and Control  
Indeed, the LBPP capacity to discriminate face components, the small size of 2DDCT features vector, and the efficiency of used classifiers, allow justifying the proposed approach's good performance.  ...  In addition, obtained features dataset will be classified using relevant machine learning classifiers. To access our solution, we applied it on ORL, Yale and AR face databases.  ...  Figures 7, shows respectively the obtained images using LBP and different variants of LBPP according to the confidence intervals size defined by: k = 1, 2, 3 or 4.  ... 
doi:10.24507/ijicic.13.05.1721 fatcat:rfc3asx3t5cqhmfj4keuckyrxi

Abnormal image detection in endoscopy videos using a filter bank and local binary patterns

Ruwan Nawarathna, JungHwan Oh, Jayantha Muthukudage, Wallapak Tavanapong, Johnny Wong, Piet C. de Groen, Shou Jiang Tang
2014 Neurocomputing  
The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image.  ...  The method uses a "texton histogram" of an image block as features. The histogram captures the distribution of different "textons" representing various textures in an endoscopy image.  ...  Acknowledgments This work is partially supported by NSF STTR-Grant No. 0740596, 0956847, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK DK083745), and the Mayo Clinic.  ... 
doi:10.1016/j.neucom.2014.02.064 pmid:25132723 pmcid:PMC4131459 fatcat:7gqycvai2vfa5euzs3a6wjytxm

A Comparative Study of Feature Extraction Methods in Images Classification

Seyyid Ahmed Medjahed
2015 International Journal of Image Graphics and Signal Processing  
We evaluate the performance of feature extraction techniques in the context of image classification and we use both binary and multiclass classifications.  ...  It allows to represent the content of images as perfectly as possible. However, in this paper, we present a comparison protocol of several feature extraction techniques under different classifiers.  ...  We use several performance metrics such as: correct rate of classification, precision, recall, etc.  ... 
doi:10.5815/ijigsp.2015.03.03 fatcat:jwz3f4jtsffhjholmk74qik45y

Acoustic Pornography Recognition using Fused Pitch and Mel-Frequency Cepstrum Coefficients

Rasoul Banaeeyan, Hezerul Abdul Karim, Haris Lye, Mohammad Faizal Ahmad Fauzi, Sarina Mansor, John See
2019 International Journal of Technology  
More specifically, we propose to extract two types of features, (I) pitch and (II) mel-frequency cepstrum coefficients (MFCC), in order to train five different variations of the k-nearest neighbor (KNN  ...  The main objective of this paper is pornography recognition using audio features.  ...  Table 1 presents the performances of the six different KNN classifiers used in our study with respect to five performance metrics.  ... 
doi:10.14716/ijtech.v10i7.3270 fatcat:qdhkoq3ckzdrhb3vxal4tijahu

Integrated local binary pattern texture features for classification of breast tissue imaged by optical coherence microscopy

Sunhua Wan, Hsiang-Chieh Lee, Xiaolei Huang, Ting Xu, Tao Xu, Xianxu Zeng, Zhan Zhang, Yuri Sheikine, James L. Connolly, James G. Fujimoto, Chao Zhou
2017 Medical Image Analysis  
In order to improve classification accuracy, we propose novel variants of LBP features, namely average LBP (ALBP) and block based LBP (BLBP).  ...  We examined multiple types of texture features and found Local Binary Pattern (LBP) features to perform better in classifying tissues imaged by OCM.  ...  Zhou, NIH grants: R00-EB010071 and R21-EY026380 to C. Zhou, R01-GM098430 to X. Huang, and R01-CA75289-18, R01-CA178636-03 to J.G. Fujimoto and J.L. Connolly.  ... 
doi:10.1016/ pmid:28327449 pmcid:PMC5479412 fatcat:3ojvs5n3kvhfbfclgmagph2i6u

Automatic Scene Recognition through Acoustic Classification for Behavioral Robotics

Sumair Aziz, Muhammad Awais, Tallha Akram, Umar Khan, Musaed Alhussein, Khursheed Aurangzeb
2019 Electronics  
The extracted feature vector is later classified using a multi-class support vector machine (SVM), which is selected as a base classifier.  ...  ., DCASE and RWCP and achieves accuracies of 97.38 % and 94.10 % , respectively.  ...  Conflicts of Interest: The authors declare that they have no competing interests. Electronics 2019, 8, 483  ... 
doi:10.3390/electronics8050483 fatcat:wowlvweruzcsbhwxfhof5mmnie

A New GLLD Operator for Mass Detection in Digital Mammograms

N. Gargouri, A. Dammak Masmoudi, D. Sellami Masmoudi, R. Abid
2012 International Journal of Biomedical Imaging  
Artificial neural networks (ANNs), support vector machine (SVM), and k-nearest neighbors (kNNs) are, then, used for classifying masses from nonmasses, illustrating better performance of ANN classifier.  ...  Local binary pattern (LBP) operator and its variants proposed by Ojala are a powerful tool for textures classification.  ...  Sincerely thanks are adressed to MVG and VGG for sharing their source codes of LBP.  ... 
doi:10.1155/2012/765649 pmid:23365556 pmcid:PMC3539378 fatcat:4pbgkwfecjf25cqkkxepjwts5e

A Machine Learning Approach for Expression Detection in Healthcare Monitoring Systems

Muhammad Kashif, Ayyaz Hussain, Asim Munir, Abdul Basit Siddiqui, AaqifAfzaal Abbasi, Muhammad Aakif, Arif Jamal Malik, Fayez Eid Alazemi, Oh-Young Song
2021 Computers Materials & Continua  
Support vector machine (SVM), k-nearest neighbor (KNN), and Naïve Bayes (NB) are used for the classification of facial expressions using selected features.  ...  It consists of three-patch [TPLBP] and four-patch LBPs [FPLBP] based feature engineering respectively. Image representation is encoded from local patch statistics using these descriptors.  ...  Fig. 5 shows the performance of multiple classifiers such as SVM, KNN, and SMO using CK+ dataset. Tab. 6 shows the recognition rate when KNN classifier is used.  ... 
doi:10.32604/cmc.2021.014782 fatcat:tykfomfyjzatvbeocdcz75pigq

Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

Chin Poo Lee, Alan Wee Chiat Tan, Kian Ming Lim
2017 American Journal of Applied Sciences  
In addition, some widely used classification schemes and benchmark databases for evaluating performance are also discussed.  ...  Each major category is further organized into several subcategories based on the nature of gait representation.  ...  kNN Table 2 . 2 Summary of model-based approaches (motion model) Literature Gait features Classifier/distance metric Table 3 . 3 Summary of model-free approaches (appearance-based representation  ... 
doi:10.3844/ajassp.2017.252.266 fatcat:rolztijvorhkfjpv6laivlrihe
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