IET Image Processing

Image denoising is still a challenging problem in image processing. The authors propose a novel image denoising method based on a deep convolution neural network (DCNN). Different from other learning-based methods, the authors design a DCNN to achieve the noise image. Thus, the latent clear image can be achieved by separating the noise image from the contaminated image. At the training stage, the ... View full abstract»

In this paper, a novel method of active contours based on the formulation of partial differential equation (PDE) is proposed for image segmentation. The evolution equation incorporates a force term that pushes the contour towards object boundary, a regularisation term which takes into account the smoothness of the level set function and an edge term which helps to stop the contour at required boun... View full abstract»

A new local feature descriptor recursive Daubechies pattern (RDbW) is developed by defining and encoding the Daubechies wavelet decomposed center–neighbour pixel relationship in the local texture. RDbW features are applied in spatial alignment (registration) of multimodal medical images using a Procrustes analysis (PA)-based affine transformation function and the registered images are further fuse... View full abstract»

The optimisation of measurement matrix that is within the compressive sensing framework is considered in this study. Based on the fact that an information factor with smaller mutual coherence performs better, the gradient measurement matrix optimisation method is improved by an orthogonal search direction revision factor. This algorithm updates the approximation of ideal Gram matrix of information... View full abstract»

As a weakly supervised learning technique, multiple instance learning (MIL) has shown an advantage over supervised learning methods for automatic detection of diabetic retinopathy (DR): only the image-level annotation is needed to achieve both detection of DR images and DR lesions, making more graded and de-identified retinal images available for learning. However, the performance of existing stud... View full abstract»

This study demonstrates the development of vision based static hand gesture recognition system using web camera in real-time applications. The vision based static hand gesture recognition system is developed using the following steps: preprocessing, feature extraction and classification. The preprocessing stage consists of illumination compensation, segmentation, filtering, hand region detection a... View full abstract»

L0 gradient minimisation model, one of edge-aware image smoothing method, also suffers from the stair-casing effect and images with strong textures cannot be smoothed effectively and weak edges or structures will be smoothed overly. The authors propose a method to overcome these drawbacks above. To begin with, the image is subjected to non-subsampled shearlet transform to obtain high-frequency com... View full abstract»

Due to uneven illumination and dim environment in the tunnel, the monitored image is blurred, which makes it difficult to recognise the traffic status. Therefore, it is necessary to enhance the tunnel image in advance. In this study, a fast image enhancement algorithm based on imaging model constraint is proposed. First, the method uses the combination of global atmospheric light and partitioned a... View full abstract»

To improve the poor robustness and low accuracy of the existing algorithms of image splicing detection, a novel passive image forgery detection method is proposed in this study, which is based on DOCT (discrete octonion cosine transform) and Markov. By introducing the octonion and DOCT, the colour information of six image channels (the RGB model and the HSI model) can be exhaustively extracted, wh... View full abstract»

Depth images extracted by light-coding-based depth cameras are widely used to reconstruct three-dimensional scenes in recent years. However, the retrieved depth accuracy greatly influences the reconstruction quality. Here, the authors present an appropriate depth extraction method based on subpixel matching to improve the depth accuracy. The proposed method utilises nearest neighbour interpolation... View full abstract»

The vision-based lane detection is an important component of advanced driver assistance systems and it is essential for lane departure warning, lane keeping, and vehicle localisation. However, it is a challenging problem to improve the robustness of multi-lane detection due to factors, such as perspective effect, possible low visibility of lanes, and partial occlusions. To deal with these issues, ... View full abstract»

This study presents a model to effectively recognise image noise of different types and levels: impulse, Gaussian, Speckle and Poisson noise, and a mixture of multiple types of the noise. To classify image noise type, the convolutional neural network (CNN) method with backpropagation algorithm and stochastic gradient descent optimisation techniques are implemented. In order to reduce the training ... View full abstract»

Recently, kernelised correlation filter (KCF)-based trackers aroused increasing interest and achieved extremely compelling results in different competitions and benchmarks in the field of visual object tracking. However, the training mechanism of the KCF that exploits simple linear combinations of filter from the previous frame easily cause error accumulation. To overcome this problem, the authors... View full abstract»

The authors propose an automatic method for extracting objects with fine quality from photographs. The authors' method starts with finding bounding boxes that enclose potential objects, which is achievable by state-of-the-art object proposal methods. To further segment objects within obtained bounding boxes, the authors propose a new multi-pass level-set method based on saliency detection and fore... View full abstract»

Segmentation is an important step in iris recognition framework because the accuracy of the iris recognition system is affected by the segmentation of the iris. The image acquisition introduces noise artefacts such as specular reflections, eyelids/eyelashes occlusions and overlapping intensities, which makes the segmentation process difficult. An efficient method has been proposed for the segmenta... View full abstract»

License plate recognition (LPR) system plays a vital role in security applications which include road traffic monitoring, street activity monitoring, identification of potential threats, and so on. Numerous methods were adopted for LPR but still, there is enough space for a single standard approach which can be able to deal with all sorts of problems such as light variations, occlusion, and multi-... View full abstract»

Optical coherence tomography is an immersive technique for depth analysis of retinal layers. Automatic choroid layer segmentation is a challenging task because of the low contrast inputs. Existing methodologies carried choroid layer segmentation manually or semi-automatically. The authors proposed automated choroid layer segmentation based on normalised cut algorithm, which aims at extracting the ... View full abstract»

Magnetic resonance imaging (MRI) and positron emission tomography (PET) image fusion is a recent hybrid modality used in several oncology applications. The MRI image shows the brain tissue anatomy and does not contain any functional information, while the PET image indicates the brain function and has a low spatial resolution. A perfect MRI–PET fusion method preserves the functional information of... View full abstract»

Even though face recognition is one of the most studied pattern recognition problems, most existing solutions still lack efficiency and high speed. Here, the authors present a new framework for face recognition which is efficient, fast, and robust against variations of illumination, expression, and pose. For feature extraction, the authors propose extracting Gabor features in order to be resilient... View full abstract»

In this paper, a new technique for plane detection from 3D point clouds is proposed. The algorithm depends on two concepts to balance between high-accuracy and fast performance. The first is the use of a new fast octree-based balanced density down-sampling technique to reduce the number of points. The second is the fact that the number of planes in any dataset is much less than the number of the p... View full abstract»

Line detection in handwritten documents is an important problem for processing of scanned documents. While existing approaches mainly use hand-designed features or heuristic rules to estimate the location of text lines, the authors present a novel approach that trains a fully convolutional network (FCN) to predict text line structure in document images. A rough estimation of text line, or a line m... View full abstract»

Here, a hybrid feature descriptor-based method is proposed to recognise human emotions from their facial expressions. A combination of spatial bag of features (SBoFs) with spatial scale-invariant feature transform (SBoF-SSIFT), and SBoFs with spatial speeded up robust transform are utilised to improve the ability to recognise facial expressions. For classification of emotions, <i>K</i>... View full abstract»

A fast adaptive and selective mean filter is presented to remove salt and pepper noise effectively from images corrupted with higher noise densities. The algorithm achieves better results in terms of visual quality and in terms of peak signal-to-noise ratio, mean absolute error, mean structural similarity index measure, image enhancement factor, and edge preservation ratio than many existing state... View full abstract»

The authors propose a new single image dehazing method. Different from image restoration and image enhancement method, their method is based on the idea of image fusion. Image dehazing is to remove the influence of the haze between the scene and the camera. First, combined with the depth information, the haze layer is subtracted in the hazy image to improve the colour saturation, which produces th... View full abstract»

Three-dimensional (3D) images have become increasingly popular in practice. They are commonly used in medical imaging applications. In such applications, it is often critical to compare two 3D images, or monitor a sequence of 3D images. To make the image comparison or image monitoring valid, the related 3D images should be geometrically aligned first, which is called image registration (IR). Howev... View full abstract»

Chessboard corner detection is a necessary procedure of the popular chessboard pattern-based camera calibration technique, in which the inner corners on a two-dimensional chessboard are employed as calibration markers. In this study, an automatic chessboard corner detection algorithm is presented for camera calibration. In authors' method, an initial corner set is first obtained with an improved H... View full abstract»

Sobriety test, which commonly uses a breathalyser for estimating blood alcohol content (BAC) from a breath sample, is commonly used to detect drunk driving. The detection often gives rise to sanitary concern and violation of human right. This research proposes a new method that employs non-invasive measurement of photoplethysmography (PPG) signal for detecting BAC of the test subject under the sob... View full abstract»

A novel framework is developed for the modelling and clustering of proportional data (i.e. normalised histograms) based on the Beta-Liouville mixture model. This framework is based on incremental model selection, by testing if a given component was truly Beta-Liouville distributed. Specifically, the authors compare the theoretical maximum entropy of the given component with the estimated entropy o... View full abstract»

Histopathology image segmentation is an important area in the field of computer aided diagnosis using image processing. This study presents a local feature-based novel technique for the segmentation of histopathology images. It mainly focuses on a system that segments overlapped nuclei (OLN) without affecting the general non-OLN segmentation performance. The proposed method suggests a three-stage ... View full abstract»

This study presents a geometric deformable model-based segmentation approach to segmentation of the intima and media-adventitial (MA) borders in sequential intravascular ultrasound (IVUS) images. The initial estimation of the vessel borders was done manually only for the first frame of each sequence. After the border initialisation, pre-processing including edge preservation, noise reduction, and ... View full abstract»

With the advancement of image editing tools in today's world, the manipulation of images like cropping, cloning, resizing, etc., becomes an easy proposition and on the other end, checking or determining whether an image has been manipulated or not, becomes a great challenge. Copy-move forgery in images is the most popular tampering method in which a portion of an image is copied and pasted in some... View full abstract»

To overcome the drawbacks of existing filters for salt and pepper noises, an adaptive probability filter is proposed. For an image, it detects salt and pepper noises based on the characteristic of minimum and maximum intensity values of the images, as well as the distribution of noise. If the noise-free intensities in neighbourhood repeat with a certain probability, the noise-free intensity with h... View full abstract»

Images degraded by haze usually have low contrast and fide colours, and thus have bad effects on applications such as object tracking, face recognition, and intelligent surveillance. So the purpose of dehazing is to recover the image contrast without colour distortion. The dark channel prior (DCP) is widely used in the field of haze removal because of its simplicity and effectiveness. However, whe... View full abstract»

According to the characteristic of pepper-and-salt noise, the authors first classify pixels in a polluted image into two classes: suspected noise and noise-free pixels. For a suspected noisy pixel, by counting the number of closed grey-level and noise-free pixels in a neighbourhood, one can correctly determine a noise or a noise-free pixel. Noise filtering does not process noise-free pixels. For t... View full abstract»

Salient object detection is a fundamental problem and has been received a great deal of attention in computer vision. Recently, deep learning model became a powerful tool for image feature extraction. In this study, the authors propose a multi-scale deep neural network (MSDNN) for salient object detection. The proposed model first extracts global high-level features and context information over th... View full abstract»

In this study, a novel adaptive sparse representation (ASR) model is presented for simultaneous image fusion and denoising. As a powerful signal modelling technique, sparse representation (SR) has been successfully employed in many image processing applications such as denoising and fusion. In traditional SR-based applications, a highly redundant dictionary is always needed to satisfy signal recon... View full abstract»

Rain image enhancement is important for outdoor computer vision applications. In this study, the authors propose a multi-stage filtering method for single rainy image enhancement. It is based on their new rainy image model, and consists of two main operations: rain streaks removal and rain fog removal. For rain streaks removal, based on one key observation that the low-pass version of a rainy imag... View full abstract»

Biometrics authentication is considered as most secure and reliable method to recognise and identify person's identity. Researchers put efforts to find efficient ways to secure and classify the solutions to biometric problems. In this category, fingerprint recognition (FPR) is most widely used biometric trait for person identification/verification. The present work focuses an FPR technique, which ... View full abstract»

Denoising of hyperspectral images is an essential step to remove the visual artifacts and improve the quality of an image. There are various sources of noise such as dark current, thermal and read noise produced due to detectors, stochastic error of photo-counting and so on which leads to variability of noise both in spatial and spectral domains. In this study, author proposes a novel denoising me... View full abstract»

This study presents a chaos-based crypto-compression scheme to protect the H.264 advanced video coding (AVC) used for the applications of video conference. To this end, a selective encryption approach was adopted. The authors proposed to encrypt the inter-prediction, the intra-prediction and the context adaptive variable length coding. The format compliance and compression ratio are conserved. The... View full abstract»

This study introduces an encryption algorithm for colour RGB images and text, the encryption is based on the synchronisation of fractional chaotic systems, the synchronisation has the topology of master–slave, where the transmitter is the master system and the receiver is the slave system, this last one is designed as a new smoothed sliding modes state observer for fractional chaotic systems. The ... View full abstract»

Lung field defines a region-of-interest in which specific radiologic signs such as septal lines, pulmonary opacities, cavities, consolidations, and lung nodules are searched by a chest radiographic computer-aided diagnostic system. Thus, its precise segmentation is extremely important. To precisely segment it, numerous methods have been developed during the last four decades. However, no exclusive... View full abstract»

Non-rigid point set registration is a key component in many computer vision and pattern recognition tasks. In this study, the authors propose a robust non-rigid point set registration method based on high-dimensional representation. Their central idea is to map the point sets into a high-dimensional space by integrating the relative structure information into the coordinates of points. On the one ... View full abstract»

Lane detection and tracking is the basic component of many intelligent vehicle systems. In this study, a robust multilane detection and tracking method is proposed. Using the measurements provided by an in-vehicle mono-camera and a forward-looking LIDAR, this algorithm can address challenging scenarios in real urban driving situations. The proposed approach makes use of steerable filters for lane ... View full abstract»

Digital watermarking has been suggested as a way to achieve digital protection. The aim of digital watermarking is to insert the secret data into the image without significantly affecting the visual quality. This study presents a robust block-based image watermarking scheme based on the singular value decomposition (SVD) and human visual system in the discrete wavelet transform (DWT) domain. The p... View full abstract»

Side scan sonar (SSS) image matching plays an important role in underwater applications, such as combining images to form wide range relief images, underwater simultaneous location and mapping, and construction of images of underwater terrain and objects. Because there are differences between the imaging mechanisms of SSS images and optical images, current matching algorithms for optical images do... View full abstract»

In this study, the perceptual video quality (PVQ) for the vogue 360-degree video with compression artefacts viewed on the visual reality (VR) head-mounted display (HMD) is obtained for the first time by an elaborately designed subjective experiment. The characteristic of the PVQ of omnidirectional (360-degree) video on the VR HMD and PC monitor is then investigated. The PVQ on the HMD is found to ... View full abstract»

This study presents a lossless robust data hiding scheme based on significance-bit-difference expansion. The original cover image can be recovered without any distortion after the hidden data have been extracted if the stego image remains intact, on the other hand, the hidden data can be robust against unintentional changes applying to the stego image, such as image compression and sometimes unavo... View full abstract»

A novel approach to detect and localise anomalous events in crowed scenes by processing surveillance videos is introduced in this study. Unusual events are those that significantly differ from current dominated behaviours. The proposed approach both detects pixel-level and block-level anomalies. In pixel level, Gaussian mixture models are used to detect abnormalities. Block-level detection segment... View full abstract»

Super-resolution (SR) task has become an important research area due to the rapidly growing interest for high quality images in various computer vision and pattern recognition applications. This has led to the emergence of various SR approaches. According to the number of input images, two kinds of approaches could be distinguished: single or multi-input based approaches. Certainly, processing mul... View full abstract»