New framework for person-independent facial expression recognition combining textural and shape analysis through new feature extraction approach
Automatic facial expression recognition (FER) has been extensively studied owing to its
wide range of applications, such as in e-learning platforms used to automatically collect the …
wide range of applications, such as in e-learning platforms used to automatically collect the …
Computer Vision‐Based Patched and Unpatched Pothole Classification Using Machine Learning Approach Optimized by Forensic‐Based Investigation Metaheuristic
During the phase of periodic asphalt pavement survey, patched and unpatched potholes
need to be accurately detected. This study proposes and verifies a computer vision‐based …
need to be accurately detected. This study proposes and verifies a computer vision‐based …
Concrete spalling severity classification using image texture analysis and a novel jellyfish search optimized machine learning approach
During the phase of building survey, spalling and its severity should be detected as earlier
as possible to provide timely information on structural heath to building maintenance …
as possible to provide timely information on structural heath to building maintenance …
A compact multi-pattern encoding descriptor for texture classification
Binary pattern family is considered as a powerful tool for visual texture classification. Most
popular methods improve the classification performance by multi-feature fusion. However …
popular methods improve the classification performance by multi-feature fusion. However …
Petersen graph multi-orientation based multi-scale ternary pattern (PGMO-MSTP): an efficient descriptor for texture and material recognition
Classifying and modeling texture images, especially those with significant rotation,
illumination, scale, and view-point variations, is a hot topic in the computer vision field …
illumination, scale, and view-point variations, is a hot topic in the computer vision field …
Towards non-data-hungry and fully-automated diagnosis of breast cancer from mammographic images
H Ghazouani, W Barhoumi - Computers in Biology and Medicine, 2021 - Elsevier
Analysing local texture and generating features are two key issues for automatic cancer
detection in mammographic images. Recent researches have shown that deep neural …
detection in mammographic images. Recent researches have shown that deep neural …
Microstructure image classification: A classifier combination approach using fuzzy integral measure
In recent times, machine learning-based methods have gained popularity in various
materials science applications including microstructure image classification. This paper …
materials science applications including microstructure image classification. This paper …
Evolutionary-based generation of rotation and scale invariant texture descriptors from SIFT keypoints
To describe image data, prominent keypoints are commonly detected before running an
extraction process to generate a feature vector. However, producing a reliable set of features …
extraction process to generate a feature vector. However, producing a reliable set of features …
Multi-scale continuous gradient local binary pattern for leaky cable fixture detection in high-speed railway tunnel
Y Zhang, Z Song, W Guo - IEEE Access, 2021 - ieeexplore.ieee.org
The feature of leaky cable fixture extracted by Local Binary Pattern (LBP) and its variants in
high-speed railway tunnel has the defects of lacking description and high dimension. This …
high-speed railway tunnel has the defects of lacking description and high dimension. This …
Wavelet domain majority coupled binary pattern: a new descriptor for texture classification
S Nithya, S Ramakrishnan - Pattern Analysis and Applications, 2021 - Springer
In this paper, a new approach for texture classification called wavelet domain majority
coupled binary pattern is proposed. Here, the single-level wavelet transform is applied …
coupled binary pattern is proposed. Here, the single-level wavelet transform is applied …