EURASIP Journal on Image and Video Processing

http://link.springer.com/journal/13640

List of Papers (Total 525)

Sea-skyline-based image stabilization of a buoy-mounted catadioptric omnidirectional vision system

Marine monitoring systems have the requirements of a large field of view, low power consumption, real-time viewing, and economical and automatic functionality. This paper establishes an omnidirectional vision system used in marine buoys that meets these requirements. We present a framework for image stabilization, which is achieved by omnidirectional sea-skyline detection in a...

Textline detection in degraded historical document images

This paper presents a textline detection method for degraded historical documents. Our method follows a conventional two-step procedure that the binarization is first performed and then the textlines are extracted from the binary image. In order to address the challenges in historical documents such as document degradation, structure noise, and skews, we develop new methods for...

Inner lips feature extraction based on CLNF with hybrid dynamic template for Cued Speech

In previous French Cued Speech (CS) studies, one of the widely used methods is painting blue color on the speaker’s lips to make lips feature extraction easier. In this paper, in order to get rid of this artifice, a novel automatic method to extract the inner lips contour of CS speakers is presented. This method is based on a recent facial contour extraction model developed in...

A framework of human detection and action recognition based on uniform segmentation and combination of Euclidean distance and joint entropy-based features selection

Human activity monitoring in the video sequences is an intriguing computer vision domain which incorporates colossal applications, e.g., surveillance systems, human-computer interaction, and traffic control systems. In this research, our primary focus is in proposing a hybrid strategy for efficient classification of human activities from a given video sequence. The proposed...

Dynamic and robust method for detection and locating vehicles in the video images sequences with use of image processing algorithm

There are various methods in the field of moving-object tracking in the video images that each of them implies on the specific features of object. Among tracking methods based on features, algorithms based on color are able to provide a precise description of the object and track the object with high speed. One of the efficient methods in the field of object tracking based on...

Design of mobile augmented reality game based on image recognition

The work studied a complete set of development system for mobile augmented reality game based on combination of AR technology and RTS game. An effective image recognition strategy was proposed through SIFT feature matching algorithm. Integrated with cloud image recognition module, the response speed of image recognition module was improved by eliminating error matching point...

Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning

Human activity recognition requires both visual and temporal cues, making it challenging to integrate these important modalities. The usual schemes for integration are averaging and fixing the weights of both features for all samples. However, how much weight is needed for each sample and modality, is still an open question. A mixture of experts via a gating Convolutional Neural...

Fast and adaptive mode decision and CU partition early termination algorithm for intra-prediction in HEVC

High Efficiency Video Coding (HEVC or H.265), the latest international video coding standard, displays a 50% bit rate reduction with nearly equal quality and dramatically higher coding complexity compared with H.264. Unlike other fast algorithms, we first propose an algorithm that combines the CU coding bits with the reduction of unnecessary intra-prediction modes to decrease...

Variational Bayesian blind restoration reconstruction based on shear wave transform for low-dose medical CT image

A variational Bayesian blind restoration reconstruction based on shear wave transform for low-dose medical computed tomography (CT) image is proposed. The proposed algorithm eliminates the effects of the point spread function in the process of low-dose medical CT image reconstruction and improves the reconstructed image quality. The shear wave transform is used to sparsely...

Relationship between entropy and SNR changes in image enhancement

There are many techniques of image enhancement. Their parameters are traditionally tuned by maximization of SNR criterion, which is unfortunately based on the knowledge of an ideal image. Our approach is based on Hartley entropy, its estimation, and differentiation. Resulting gradient of entropy is estimated without knowledge of ideal images, and it is a subject of minimization...

Recognition of identical twins using fusion of various facial feature extractors

Distinguishing identical twins using their face images is a challenge in biometrics. The goal of this study is to construct a biometric system that is able to give the correct matching decision for the recognition of identical twins. We propose a method that uses feature-level fusion, score-level fusion, and decision-level fusion with principal component analysis, histogram of...

A fast framework construction and visualization method for particle-based fluid

Fast and vivid fluid simulation and visualization is a challenge topic of study in recent years. Particle-based simulation method has been widely used in the art animation modeling and multimedia field. However, the requirements of huge numerical calculation and high quality of visualization usually result in a poor computing efficiency. In this work, in order to improve those...

Predicting students’ attention in the classroom from Kinect facial and body features

This paper proposes a novel approach to automatic estimation of attention of students during lectures in the classroom. The approach uses 2D and 3D data obtained by the Kinect One sensor to build a feature set characterizing both facial and body properties of a student, including gaze point and body posture. Machine learning algorithms are used to train classifiers which estimate...

A feature fusion based localized multiple kernel learning system for real world image classification

Real-world image classification, which aims to determine the semantic class of un-labeled images, is a challenging task. In this paper, we focus on two challenges of image classification and propose a method to address both of them simultaneously. The first challenge is that representing images by heterogeneous features, such as color, shape and texture, helps to provide better...

Efficient AMP decision and search range adjustment algorithm for HEVC

The advanced video encoder High Efficiency Video Coding (HEVC) utilizes several novel coding tools so that it can obtain improvement in coding performance for a huge number of video data. However, these tools increase the computational complexity greatly specially in the interprediction phase. Therefore, optimization for interprediction plays an important role in accelerating the...

Exploiting textures for better action recognition in low-quality videos

Human action recognition is an increasingly matured field of study in the recent years, owing to its widespread use in various applications. A number of related research problems, such as feature representations, human pose and body parts detection, and scene/object context, are being actively studied. However, the general problem of video quality—a realistic issue in the face of...

Visual object tracking based on Motion-Adaptive Particle Filter under complex dynamics

This paper presents a novel particle filter called Motion-Adaptive Particle Filter (MAPF) to track fast-moving objects that have complex dynamic movements. The objective was to achieve effectiveness and robustness against abrupt motions and affine transformations. To that end, MAPF first predicted both velocity and acceleration according to prior data of the tracked objects, and...

Multi-domain and multi-task prediction of extraversion and leadership from meeting videos

Automatic prediction of personalities from meeting videos is a classical machine learning problem. Psychologists define personality traits as uncorrelated long-term characteristics of human beings. However, human annotations of personality traits introduce cultural and cognitive bias. In this study, we present methods to automatically predict emergent leadership and personality...

Content and buffer status aware packet scheduling and resource management framework for video streaming over LTE system

With the development of the video encoding and wireless communication technologies, DASH (Dynamic Adaptive Streaming over HTTP) services have an increasing and great share of all the mobile services. However, we find some problems which still need to be addressed for DASH service optimization: (1) the limitation of the video segment representations cannot keep pace with the...

A multiscale modified minimum spanning forest method for spatial-spectral hyperspectral images classification

This paper aimed to present a new method for the spectral-spatial classification of hyperspectral images, based on the idea of modified minimum spanning forest (MMSF). MMSF works on the obtained regions of pre-segmentation step that are considered as nodes of an image graph. In the proposed method, the image is first smoothed by the multiscale edge-preserving filter (MSEPF) and...

Time-dependent bag of words on manifolds for geodesic-based classification of video activities towards assisted living and healthcare

In this paper, we address the problem of classifying activities of daily living (ADL) in video. The basic idea of the proposed method is to treat each human activity in the video as a temporal sequence of points on a Riemannian manifold and classify such time series with a geodesic-based kernel. The main novelties of this paper are summarized as follows: (a) for each frame of a...

Double regularization medical CT image blind restoration reconstruction based on proximal alternating direction method of multipliers

To solve the problem of CT image degradation, a double regularization CT image blind restoration reconstruction method was proposed. The objective function including both a clear image and point spread function was established. To avoid the over-smoothing phenomenon and protect the detail, the objective function includes two constraint regularization terms. They are total...

A fast source-oriented image clustering method for digital forensics

We present in this paper an algorithm that is capable of clustering images taken by an unknown number of unknown digital cameras into groups, such that each contains only images taken by the same source camera. It first extracts a sensor pattern noise (SPN) from each image, which serves as the fingerprint of the camera that has taken the image. The image clustering is performed...

JPEG Privacy and Security framework for social networking and GLAM services

Current image coding standards provide limited support for privacy and security features. An exception is the JPSEC standard, which defines security extensions in JPEG 2000 specifications (part 8). Notwithstanding this shortcoming, the JPEG committee is currently defining a new JPEG Systems standard, which envisages privacy and security support across JPEG family of standards. In...

An adaptive decision based interpolation scheme for the removal of high density salt and pepper noise in images

An adaptive decision based inverse distance weighted interpolation (DBIDWI) algorithm for the elimination of high-density salt and pepper noise in images is proposed. The pixel is initially checked for salt and pepper noise. If classified as noisy pixel, replace it with an inverse distance weighted interpolation value. This interpolation estimates the values of corrupted pixels...