Genetic programming-based fusion of HOG and LBP features for fully automated texture classification
Classifying texture images relies heavily on the quality of the extracted features. However,
producing a reliable set of features is a difficult task that often requires human intervention to …
producing a reliable set of features is a difficult task that often requires human intervention to …
PCB component detection using computer vision for hardware assurance
Printed circuit board (PCB) assurance in the optical domain is a crucial field of study.
Though there are many existing PCB assurance methods using image processing, computer …
Though there are many existing PCB assurance methods using image processing, computer …
Local ternary pattern based multi-directional guided mixed mask (MDGMM-LTP) for texture and material classification
Local feature descriptors (LFDs) have been researched and developed for decades, and
their applications are still being examined nowadays. In addition, the fact that LFDs are …
their applications are still being examined nowadays. In addition, the fact that LFDs are …
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 …
A robust wavelet domain multi-scale texture descriptor for image classification
X Wang, L Feng, D Wang, P Niu - Expert Systems with Applications, 2025 - Elsevier
Local binary pattern (LBP) and many variants adopt the difference information to encode all
the neighborhood binarization, demonstrating excellent ability to distinguish images …
the neighborhood binarization, demonstrating excellent ability to distinguish images …
New local binary pattern approaches based on color channels in texture classification
In this paper, four novel, simple and robust approaches, which are left to right local binary
patterns (LBPL L2R), top to down local binary patterns (LBP T2D), cube surface local binary …
patterns (LBPL L2R), top to down local binary patterns (LBP T2D), cube surface local binary …
A deep learning-based and adaptive region proposal algorithm for semantic segmentation
M Taghizadeh, A Chalechale - Applied Soft Computing, 2024 - Elsevier
This paper presents an adaptive and new region proposal algorithm for generating high-
quality regions. The main aim of this algorithm is to investigate different features in the …
quality regions. The main aim of this algorithm is to investigate different features in the …
An expeditious HPLC method to distinguish Aconitum kusnezoffii from related species
Y Zhao, Y Zhang, R Lin, W Sun - Fitoterapia, 2009 - Elsevier
An optimized HPLC-DAD method aided by similarity and hierarchical clustering analysis
(HCA) was applied for identification of four species of the roots of Aconitum. The unique …
(HCA) was applied for identification of four species of the roots of Aconitum. The unique …
Application of optimized local binary pattern algorithm in small pose face recognition under machine vision
H Qu, Y Wang - Multimedia Tools and Applications, 2022 - Springer
With the development of information technology, face recognition technology is becoming
more robust against the influence of illumination, pose, and noise. The purpose is to study …
more robust against the influence of illumination, pose, and noise. The purpose is to study …
Completed homogeneous LBP for remote sensing image classification
I Al Saidi, M Rziza, J Debayle - International Journal of Remote …, 2023 - Taylor & Francis
Land cover (LC) classification remains a challenging task due to the diversity of terrain and
topography, limited prior knowledge, and complex data sets. These variations can lead to …
topography, limited prior knowledge, and complex data sets. These variations can lead to …