EURASIP Journal on Image and Video Processing

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

List of Papers (Total 525)

A novel search method based on artificial bee colony algorithm for block motion estimation

The large amount of bandwidth that is required for the transmission or storage of digital videos is the main incentive for researchers to develop algorithms that aim at compressing video data while keeping their quality as high as possible. Block matching has been extensively utilized in compression algorithms for motion estimation as they reduce the memory requirements of any...

Classification of lung sounds using convolutional neural networks

In the field of medicine, with the introduction of computer systems that can collect and analyze massive amounts of data, many non-invasive diagnostic methods are being developed for a variety of conditions. In this study, our aim is to develop a non-invasive method of classifying respiratory sounds that are recorded by an electronic stethoscope and the audio recording software...

Quantitative comparison of motion history image variants for video-based depression assessment

Depression is the most prevalent mood disorder and a leading cause of disability worldwide. Automated video-based analyses may afford objective measures to support clinical judgments. In the present paper, categorical depression assessment is addressed by proposing a novel variant of the Motion History Image (MHI) which considers Gabor-inhibited filtered data instead of the...

Improved reversible data hiding in JPEG images based on new coefficient selection strategy

Recently, reversible data hiding (RDH) techniques for JPEG images have become more extensively used to combine image and authentication information conveniently into one file. Although embedding data in JPEG image degrades visual quality and increases file size, it is proven to be useful for data communication and image authentication. In this paper, a data hiding method in JPEG...

Segmentation-free optical character recognition for printed Urdu text

This paper presents a segmentation-free optical character recognition system for printed Urdu Nastaliq font using ligatures as units of recognition. The proposed technique relies on statistical features and employs Hidden Markov Models for classification. A total of 1525 unique high-frequency Urdu ligatures from the standard Urdu Printed Text Images (UPTI) database are considered...

Stereoscopic visual saliency prediction based on stereo contrast and stereo focus

In this paper, we exploit two characteristics of stereoscopic vision: the pop-out effect and the comfort zone. We propose a visual saliency prediction model for stereoscopic images based on stereo contrast and stereo focus models. The stereo contrast model measures stereo saliency based on the color/depth contrast and the pop-out effect. The stereo focus model describes the...

Predicting the Sixteen Personality Factors (16PF) of an individual by analyzing facial features

We propose a novel three-layered neural network-based architecture for predicting the Sixteen Personality Factors from facial features analyzed using Facial Action Coding System. The proposed architecture is built on three layers: a base layer where the facial features are extracted from each video frame using a multi-state face model and the intensity levels of 27 Action Units...

Robust MRI abnormality detection using background noise removal with polyfit surface evolution

Image segmentation plays a vital role in MRI abnormality detection. This paper presents a robust MRI segmentation method to outline potential abnormality blobs. Thresholding and boundary tracing strategies are employed to remove background noises, and hence, the ROIs in the whole process are set. Subsequently, a polyfit surface evolution is proposed to approximately estimate bias...

Surface editing using swept surface 3D models

This paper presents a system for editing strip-like patches on the mesh using swept surface. The user first selects a rough cylinder-like region, the boundary of which is automatically refined. A swept surface approximation is automatically done, including extraction of the trajectory and the corresponding deforming 2D curves. The swept surface is described by a map from a real...

Patch-based models and algorithms for image denoising: a comparative review between patch-based images denoising methods for additive noise reduction

Background Digital images are captured using sensors during the data acquisition phase, where they are often contaminated by noise (an undesired random signal). Such noise can also be produced during transmission or by poor-quality lossy image compression. Reducing the noise and enhancing the images are considered the central process to all other digital image processing tasks...

A two-stage algorithm for the early detection of zero-quantized discrete cosine transform coefficients in High Efficiency Video Coding

For High Efficiency Video Coding (HEVC) using block-based prediction, the discrete cosine transform (DCT), and quantization, a large number of DCT coefficients in a transform block (TB) are commonly found to be quantized to zero. A two-dimensional transform in HEVC is usually implemented by first applying a butterfly-based one-dimensional (1D) DCT to each row of the residual...

The application of multi-modality medical image fusion based method to cerebral infarction

A multi-modality image fusion can process images of certain organs or issues which were collected from diverse medical imaging equipment. The fusion can extract complementary information and integrate into images with more comprehensive information. The multi-modality image fusion can provide image that was combined with anatomical and physiological information for doctors and...

COGNIMUSE: a multimodal video database annotated with saliency, events, semantics and emotion with application to summarization

Research related to computational modeling for machine-based understanding requires ground truth data for training, content analysis, and evaluation. In this paper, we present a multimodal video database, namely COGNIMUSE, annotated with sensory and semantic saliency, events, cross-media semantics, and emotion. The purpose of this database is manifold; it can be used for training...

A robust iterative algorithm for image restoration

We present a new image restoration method by combining iterative VanCittert algorithm with noise reduction modeling. Our approach enables decoupling between deblurring and denoising during the restoration process, so allows any well-established noise reduction operator to be implemented in our model, independent of the VanCittert deblurring operation. Such an approach has led to...

Laban movement analysis and hidden Markov models for dynamic 3D gesture recognition

In this paper, we propose a new approach for body gesture recognition. The body motion features considered quantify a set of Laban Movement Analysis (LMA) concepts. These features are used to build a dictionary of reference poses, obtained with the help of a k-medians clustering technique. Then, a soft assignment method is applied to the gesture sequences to obtain a gesture...

Moving shadow detection based on stationary wavelet transform

Many surveillance and forensic applications face problems in identifying shadows and their removal. The moving shadow points overlap with the moving objects in a video sequence leading to misclassification of the exact object. This article presents a novel method for identifying and removing moving shadows using stationary wavelet transform (SWT) based on a threshold determined...

Sparse signal subspace decomposition based on adaptive over-complete dictionary

This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called “sparse signal subspace decomposition” (or 3SD) method. This method makes use of a novel criterion based on the occurrence frequency of atoms of the dictionary over the data set. This criterion, well adapted to subspace decomposition over a dependent basis set...

Low storage space for compressive sensing: semi-tensor product approach

Random measurement matrices play a critical role in successful recovery with the compressive sensing (CS) framework. However, due to its randomly generated elements, these matrices require massive amounts of storage space to implement a random matrix in CS applications. To effectively reduce the storage space of the random measurement matrix for CS, we propose a random sampling...

An evolutionary classifier for steel surface defects with small sample set

Nowadays, surface defect detection systems for steel strip have replaced traditional artificial inspection systems, and automatic defect detection systems offer good performance when the sample set is large and the model is stable. However, the trained model does work well when a new production line is initiated with different equipment, processes, or detection devices. These...

Estimation of Bayer CFA pattern configuration based on singular value decomposition

An image sensor can measure only one color per pixel through the color filter array. Missing pixels are estimated using an interpolation process. For this reason, a captured pixel and interpolated pixel have different statistical characteristics. Because the pattern of a color filter array is changed when the image is manipulated or forged, this pattern change can be a clue to...

Calibration and rectification of vertically aligned binocular omnistereo vision systems

Omnidirectional stereo vision systems have been widely used as primary vision sensors in intelligent robot 3D measurement tasks, which require stereo calibration and rectification. Current stereo calibration and rectification methods suffer from complex calculations or a lack of accuracy. This paper establishes a simple and effective equivalency between an omnidirectional stereo...

The use of hidden Markov models to verify the identity based on facial asymmetry

This work concerns the use of biometric features, resulting from the look of a face, for the verification purposes. Different methods of selection and feature analysis during face recognition are presented here. The description contains mainly analysis possibilities and also identity verification based on asymmetric facial features—in later stages. The new verification method has...

Low-light image restoration using bright channel prior-based variational Retinex model

This paper presents a low-light image restoration method based on the variational Retinex model using the bright channel prior (BCP) and total-variation minimization. The proposed method first estimates the bright channel to control the amount of brightness enhancement. Next, the variational Retinex-based energy function is iteratively minimized to estimate the improved...

Noise-resistant network: a deep-learning method for face recognition under noise

Along with the developments of deep learning, many recent architectures have been proposed for face recognition and even get close to human performance. However, accurately recognizing an identity from seriously noisy face images still remains a challenge. In this paper, we propose a carefully designed deep neural network coined noise-resistant network (NR-Network) for face...

Improved gradient local ternary patterns for facial expression recognition

Automated human emotion detection is a topic of significant interest in the field of computer vision. Over the past decade, much emphasis has been on using facial expression recognition (FER) to extract emotion from facial expressions. Many popular appearance-based methods such as local binary pattern (LBP), local directional pattern (LDP) and local ternary pattern (LTP) have...