Colour image retrieval based on the hypergraph combined with a weighted adjacent structure
Content‐based image retrieval (CBIR) is a research hotspot. To improve the performance of a CBIR system, especially the retrieval accuracy, this work proposes a method that uses a soft hypergraph combined with a weighted adjacent structure (WAS) to ...
DCA‐based unimodal feature‐level fusion of orthogonal moments for Indian sign language dataset
Sign language recognition system classifies signs made by hand gestures. An adequate number of features are required to represent the shape variations of sign language. As compared to individual feature set, a combination of features can be effective due ...
Deep probabilistic human pose estimation
The authors consider the problem of human pose estimation using probabilistic convolutional neural networks. They explore ways to improve human pose estimation accuracy on standard pose estimation benchmarks MPII human pose and Leeds Sports Pose (LSP) ...
Dynamic ROI extraction method for hand vein images
The region of interest (ROI) extraction is important in hand vein recognition system. The main challenges for accurate extraction of the vein region are to overcome variability in hand size, lighting conditions, orientation, appearance, noisy background, ...
Real‐time segmentation of various insulators using generative adversarial networks
The conventional inspection of fragile insulators is critical to grid operation and insulator segmentation is the basis of inspection. However, the segmentation of various insulators is still difficult because of the great differences in colour and shape, ...
Angled local directional pattern for texture analysis with an application to facial expression recognition
Local binary pattern (LBP) is currently one of the most common feature extraction methods used for texture analysis. However, LBP suffers from random noise, because it depends on image intensity. Recently, a more stable feature method was introduced, ...
Automatic lung segmentation based on Graph Cut using a distance‐constrained energy
Lung segmentation serves to ensure that all the parts of the lungs are considered during pulmonary image analysis by isolating the lung from the surrounding anatomy in the image. Research has shown that computed tomography (CT) images greatly improves the ...
Multi‐bit quantisation for similarity‐preserving hashing
As a promising alternative to traditional search techniques, hashing‐based approximate nearest neighbour search provides an applicable solution for big data. Most existing efforts are devoted to finding better projections to preserve the neighbouring ...
Automatic adaptation of SIFT for robust facial recognition in uncontrolled lighting conditions
The scale invariant feature transform (SIFT), which was proposed by David Lowe, is a powerful method that extracts and describes local features called keypoints from images. These keypoints are invariant to scale, translation, and rotation, and partially ...
Tracking objects with co‐occurrence matrix and particle filter in infrared video sequences
Tracking objects in infrared video sequences became a very important challenge for many current tracking algorithms due to several complex situations such as illumination variation, night vision, and occlusion. This study proposes a new tracker that uses ...
Robust video tracking algorithm: a multi‐feature fusion approach
This study proposes a novel robust video tracking algorithm consists of target detection, multi‐feature fusion, and extended Camshift. Firstly, a novel target detection method that integrates Canny edge operator, three‐frame difference, and improved ...
Precise depth map upsampling and enhancement based on edge‐preserving fusion filters
A texture image plus its associated depth map is the simplest representation of a three‐dimensional image and video signals and can be further encoded for effective transmission. Since it contains fewer variations, a depth map can be coded with much lower ...
Dimensionality reduction by LPP‐L21
Locality preserving projection (LPP) is one of the most representative linear manifold learning methods and well exploits intrinsic structure of data. However, the performance of LPP remarkably degenerate in the presence of outliers. To alleviate this ...
Data‐driven recovery of hand depth using CRRF on stereo images
Hand pose is emerging as an important interface for human–computer interaction. This study presents a data‐driven method to estimate a high‐quality depth map of a hand from a stereoscopic camera input by introducing a novel superpixel‐based regression ...
Animal classification using facial images with score‐level fusion
A real‐world animal biometric system that detects and describes animal life in image and video data is an emerging subject in machine vision. These systems develop computer vision approaches for the classification of animals. A novel method for animal ...
Detecting heel strikes for gait analysis through acceleration flow
In some forms of gait analysis, it is important to be able to capture when the heel strikes occur. In addition, in terms of video analysis of gait, it is important to be able to localise the heel where it strikes on the floor. In this study, a new motion ...
Accuracy assessment of single viewing techniques for metric measurements on single images
Single view methodology has been a long‐standing issue of extracting metric information from a single image in the relevant disciplines. To perform metric measurements on a single image, two methods, which are based on identifying vanishing points (VPs), ...
High‐level feature aggregation for fine‐grained architectural floor plan retrieval
Due to the massive growth of real estate industry, there is an increase in the number of online platforms designed for finding homes/furnished properties. Instead of descriptive words, query by example is always a preferred method for retrieval. Floor ...
Multi‐dimensional long short‐term memory networks for artificial Arabic text recognition in news video
This study presents a novel approach for Arabic video text recognition based on recurrent neural networks. In fact, embedded texts in videos represent a rich source of information for indexing and automatically annotating multimedia documents. However, ...
Single‐camera pose estimation using mirage
Recently, mirage pose estimation method was proposed for multi‐camera systems. Multi‐camera mirage analytically solves a system of linear equations for six pose parameters in O(n) time. Mirage promises to execute in real time with high accuracy and shows ...
Visual multiple‐object tracking for unknown clutter rate
In multi‐object tracking applications, model parameter tuning is a prerequisite for reliable performance. In particular, it is difficult to know statistics of false measurements due to various sensing conditions and changes in the field of views. In this ...
Action recognition based on motion of oriented magnitude patterns and feature selection
Here, the authors introduce a novel system which incorporates the discriminative motion of oriented magnitude patterns (MOMP) descriptor into simple yet efficient techniques. The authors’ descriptor both investigates the relations of the local gradient ...
Hand geometry based user identification using minimal edge connected hand image graph
In a previously reported work, the user's hand is represented as a weighted undirected complete connected graph and spectral properties of the graph are extracted and used as feature vectors. To reduce the complexity in representing the hand image as a ...
Image super‐resolution via adaptive sparse representation and self‐learning
This study proposes a novel super‐resolution regularisation model based on adaptive sparse representation and self‐learning frameworks. The fidelity term in the model ensures that the reconstructed image is consistent with the observation image. The ...
