Results 41 to 50 of about 15,252 (157)
Ground truth free retinal vessel segmentation by learning from simple pixels
IET Image Processing, 2021 Retinal vessel segmentation is fundamental for the automatic retinal image analysis and ocular disease screening. This paper aims to learn a ground truth free feature aggregation strategy for the vessel segmentation.
Beiji Zou +3 more
doaj +1 more source
Study of statistical methods for texture analysis and their modern evolutions
Engineering Reports, 2020 Texture analysis is widely performed in the current time as it is considered as an intimate property of the surface. It is widely used in the field of image processing, remote sensing applications, biomedical analysis, document processing, and so on.
Ayushman Ramola +2 more
doaj +1 more source
Ensemble feature selection approach based on feature ranking for rice seed images classification
Advances in Electrical and Electronic Engineering, 2020 In smart agriculture, rice variety inspection systems based on computer vision need to be used for recognizing rice seeds instead of using technical experts.
Dzi Lam Tran Tuan +3 more
doaj +1 more source
A Sparse Representation of Complete Local Binary Pattern Histogram for Human Face Recognition
CoRR, 2016 Human face recognition has been a long standing problem in computer vision and pattern recognition. Facial analysis can be viewed as a two-fold problem, namely (i) facial representation, and (ii) classification. So far, many face representations have been proposed, a well-known method is the Local Binary Pattern (LBP), which has witnessed a growing ...
Mawloud Guermoui +1 more
openaire +2 more sources
Texture Segmentation using LBP embedded Region Competition
ELCVIA Electronic Letters on Computer Vision and Image Analysis, 2005 In this paper, we modify the region competition method to segment textures. First, local Binary pattern (LBP) histogram is adopted to capture the texture information.
Qing Xu, Jie Yang, Siyi Ding
doaj +1 more source
Local Binary Pattern Histogram for Face Recognition in Student Attendance System
2020 3rd International Conference on Computer and Informatics Engineering (IC2IE), 2020 Student attendance record has an important role in the educational process. Universitas Bhayangkara Jakarta Raya, as a case study, uses attendance record as the factor for final grade calculation. Many attendance recording systems were developed using biometrics, e.g. face recognition, iris recognition, and fingerprint recognition.
Alexander, Allan D +5 more
openaire +1 more source
Robot Vision Pattern Recognition of the Eye and Nose Using the Local Binary Pattern Histogram Method
Computer Engineering and Applications Journal, 2023 The local binary pattern histogram (LBPH) algorithm is a computer technique that can detect a person's face based on information stored in a database (trained model). In this research, the LBPH approach is applied for face recognition combined with the embedded platform on the actuator system.
Osvari Arsalan +4 more
openaire +1 more source
Local Similarity Number and its Application to Object Tracking
International Journal of Advanced Robotic Systems, 2013 In this paper, we present a tracking technique utilizing a simple saliency visual descriptor. Initially, we define a visual descriptor named local similarity pattern that mimics the famous texture operator local binary patterns.
Hamed Rezazadegan Tavakoli +2 more
doaj +1 more source
Content-independent orientation detection with histogram of optimized local binary pattern [PDF]
, 2021 This thesis is primarily concerned with the introduction of a new approach to the general problem of automatic image orientation detection. Inspired by the local binary pattern (LBP), a luminance, rotation and scale invariant and content-independent algorithm is proposed, namely: Histogram of Optimized Local Binary Pattern (HOOPLBP).
openaire +1 more source
Weighted Multi-scale Local Binary Pattern Histograms for Face Recognition
International Journal of Applied Mathematics and Informatics, 2020 This paper proposes a novel face recognition methodology, which is based on the combination of the texture operator, namely Multi-scale Local Binary Pattern (MSLBP), face image filtering and discriminative feature weighting algorithms. Presented MSLBP principle enhances the discriminative power of the original Local Binary Pattern operator.
openaire +1 more source