IET Image Processing

Steganography is used for secret or covert communication. A graph wavelet transform-based steganography using graph signal processing (GSP) is presented, which results in better visual quality stego image as well as extracted secret image. In the proposed scheme, graph wavelet transforms of both the cover image and transformed secret image (using Arnold cat map) are taken followed by alpha blendin... View full abstract»

In image denoising, high-frequency components are more notable to the human eyes than low-frequency components. While high-frequency components contain more variations and represent the detailed textures, the reconstructions of these components are much harder and it is a remaining challenge in image denoising. In this study, a novel edge-preserving image denoising algorithm is proposed, it treats... View full abstract»

The methods of the image noise reduction based on optimal channel-processing to enhance image quality are studied. According to different noise with the different ratio in colour components, different noise reduction technologies are used for noise reduction. Then the optimal algorithm is automatically selected as the ultimate way of noise reduction in each channel. For the purpose of optimal nois... 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»

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»

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»

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»

It is difficult to preserve diminishing weak structures and edges, and remove complex details simultaneously in the context of image smoothing. While most of existing methods only take either local or global features into consideration, the authors propose two methods taking advantage of both to achieve smoothing, both of which consist of two steps and share the same first step. In the first step,... View full abstract»

Background subtraction based on change detection is the first step in many video surveillance systems, an effective background subtraction algorithm should distinguish foreground from the background sensitively, and adapt to the variation of background scenes robustly. In this study, the authors propose a robust background subtraction algorithm which takes advantages of local texture features repr... 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»

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»

Visual object tracking is an important and challenging task in computer vision. In this study, the authors propose a novel visual tracking approach by decomposing the tracking task into translation and scale estimation. In translation estimation, they employ multiple adaptive correlation filters with features of hierarchical convolutional neural networks (CNNs) to more accurately estimate the targ... View full abstract»

Changes of retinal blood vessel are precursors of many serious diseases such as diabetic retinopathy, hypertension and cardiovascular diseases. Automatic segmentation of retinal blood vessels in the fundus image can better assist in the diagnosis of these diseases and has been studied by many researchers. However, the segmentation of pale vessel pixels remains a problem because of their low contra... 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»

In this study, a multiple hypothesis tracking (MHT) algorithm for multi-target multi-camera tracking (MCT) with disjoint views is proposed. The authors' method forms track-hypothesis trees, and each branch of them represents a multi-camera track of a target that may move within a camera as well as move across cameras. Furthermore, multi-target tracking within a camera is performed simultaneously w... View full abstract»

The main challenges of image encryption are robustness against attacks, key space, key sensitivity, and diffusion. To deal with these challenges, a differential evolution-based image encryption technique is proposed. In the proposed technique, two concepts are utilised to encrypt the images in an efficient manner. The first one is Arnold transform, which is utilised to permute the pixels position ... View full abstract»

Recently, image de-noising algorithm based on sparse representation has received an increasing amount of attention. Such algorithms proposed a comprehensive sparse representation model, by solving the sparse coding problem and choosing the proper method for dictionary updating to achieve better de-noising results. Therefore, the construction of learning dictionary has become one of the key problem... 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»

Development of automatic disease detection and classification system is significantly explored in precision agriculture. In the past few decades, researchers have studied several cultures exploiting different parts of a plant. A similar study is performed for Soybean using leaf images. A rule based semi-automatic system using concepts of <i>k</i>-means is designed and implemented to di... View full abstract»

This study presents a novel image-naturalness restoration for the purpose of achieving better image quality with respect to the human visual system. Specifically, the authors suppress the artefacts around edges using image gradient components. They also appropriately enhance the image brightness using an adaptive gamma correction. In particular, they simply create a mapping curve to adjust the con... 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»

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»

Traditional image stitch methods based on feature point detection require long registration time for high resolution images. In the SIFT (scale invariant feature transform) algorithm, it builds difference-of-Gaussian by a linear Gauss expansion filter to obtain the feature. SIFT has poor real time. In this study, a novel image registration method based on image block is proposed to make a rough ma... 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»

In this study, the authors present quantitative quality assessment indices for measuring geometric and photometric qualities of stitched panoramic images, since both geometric and photometric qualities are important for obtaining a seamless panoramic image. For geometric quality assessment, our approach is based on the use of structural similarity (SSIM) index between the high-frequency informatio... 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»

In this review, image clustering problem is discussed starting from global learning based clustering approaches such as Kmeans to the recent challenges in this domain. In global learning based clustering models, cluster evaluation criteria was formulated on whole image datasets. In local learing based clustering models, local neighbourhood information in image data matrices were utilised. However,... View full abstract»

A novel general-purpose no-reference image quality assessment (NR-IQA) model utilising hybrid natural scene statistics (HNSS) is proposed. Distinguished from existing NR-IQA approaches, the new model combines the statistics of locally mean subtracted and contrast normalised coefficients in the spatial domain and the statistics of image patch coefficients in a codebook space, which is constructed b... View full abstract»

An adaptive plateau limit-based histogram equalisation algorithm is suggested to enhance digital images. Histogram of the image is clipped with a plateau limit to avoid over enhancement. The plateau limit is derived from the average of the mean and the median intensity values to offer the improved enhancement. Clipped histogram is subdivided into three parts, using histogram subdivision limit para... View full abstract»

The following article published in IET Image Processing, Shahid, Muhammad; Taj, Imtiaz A.: ‘Robust retinal vessel segmentation using vessels location map and Frangi enhancement filter’, IET Image Processing, 2018, DOI: 10.1049/iet-ipr.2017.0457 on 16th January 2018 has been retracted due to a breach of the IET's Policy in Relation to Plagiarism, Infringement of Copyright and Infringement of Moral ... View full abstract»

Wavelet-based segmentation approaches are widely used for texture segmentation purposes because of their ability to characterise different textures. In this study, the authors assess the influence of the chosen wavelet and propose to use the recently introduced empirical wavelets. We show that the adaptability of the empirical wavelet permits to reach better results than classic wavelets. To focus... View full abstract»

Here, the authors explore the potential of multispectral imaging applied to image completion. Snapshot multispectral cameras correspond to breakthrough technologies that are suitable for everyday use. Therefore, they correspond to an interesting alternative to digital cameras. In their experiments, multispectral images are acquired using an ultracompact snapshot camera-recorder that senses 16 diff... View full abstract»

Forgery detection from the images is gaining remarkable interest as there are a lot of editing tools that enable to cause edition with manipulation or removal of the objects from the images. This study proposes a new forgery detection scheme that is based on the supervised learning approach. The supervised learning is brought about by using the support vector neural network and the optimisation is... 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»

Correlation-based pattern recognition filtering methods such as the eigenextended maximum average correlation height (EEMACH) filter is considered an effective tool in object recognition applications. However, these approaches require exclusive training for all possible distortions including in-plane as well as out-of-plane rotation, scale and illumination variations. The overall training process ... View full abstract»

To further improve the effect of infrared small target detection, a reweighted infrared patch-image model is proposed. First, the authors point out that the nuclear norm in the infrared patch-image model could easily leave some sparse background edges in the target patch-image, leading to an inaccurate background estimation. Then, to overcome this defect, the reweighted nuclear norm is adopted to ... 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»

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»

This study proposes two reversible data hiding (RDH) schemes for vector quantisation (VQ)-compressed images based on switching-tree coding (STC) and dynamic tree-coding scheme (DTCS). Most developed VQ-based RDH schemes produce non-legitimate codes as output. In order to preserve the legitimacy of the embedded VQ code, some schemes embed data into VQ indices by employing an index replacement mecha... View full abstract»

Image filtering is to retain the details of the image as much as possible and meanwhile suppress the noise pollution to great extent. This study presents an image filtering using the truncated statistics and edge preserving. In the first step of our method, the alpha-trimmed filter is utilized to remove a variety of types of noises; in the second step, taking the image after alpha-trimmed filterin... View full abstract»

A new anti-occlusion particle filter object-tracking method based on feature fusion is proposed in this study. Colour and local binary pattern features are extracted and additively fused with a deterministic coefficient, which is calculated based on the difference between the object features and the background. An integral cumulative histogram is proposed to reduce the computational cost of featur... View full abstract»

As vehicular traffic continues to grow traffic management and prevention of accidents has become a major concern. This problem only gets magnified when travel on the mountainous roads are considered. This study is especially focused toward Himalayan mountains as they pose a greater risk because of their rugged natural setting. This study investigates crucial problems faced on the hilly roads and t... View full abstract»

Advances in the eye care telemedicine system aid the diabetic patients in remote areas to stop the unwanted visit to ophthalmologist, reduces overall cost, time and money. Diabetic retinopathy, which is the primary cause of sight loss, has the most common symptoms like microaneurysms, haemorrhages, cotton-wool spots, exudates and drusen. In this work, an efficient approach for the automatic detect... 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»

Smooth filtering is a common post-operation which is exploited to blur and conceal the traces of tampered objects. Most of the existing forensic methods aim at detecting only one type of filtering process, such as median filtering or Gaussian filtering, which limits their applications. The authors present a new forensic method based on deep learning technique, which utilises a convolutional neural... View full abstract»

The authors propose an image region annotation framework by exploring syntactic and semantic correlations among segmented regions in an image. A texture-enhanced image segmentation JSEG algorithm is first used to improve the pixel consistency in a segmented image region. Next, each region is represented by a set of image codewords, also known as visual alphabets, with each of them used to characte... View full abstract»

In this study, a thorough analysis of image reconstruction in an active millimetre-wave (MMW) cylindrical imaging system is performed. To improve the system's performance in terms of the total cost as well as the coupling effect, sparse multi-static arrays are desired. Nevertheless, the existing reconstruction methods fail to operate in sparse multi-static antenna-array systems. Therefore, to addr... View full abstract»

In this study, the authors propose a new method to fuse multiple segmentations generated by different methods or same methods with different parameters. The proposed method has several contributions. First, they convert the image segmentation fusion problem into a weakly supervised learning problem. Thus, the information of superpixels can be used to guide the fusion process. Second, they treat th... View full abstract»

Automatic image classification has become a necessary task to handle the rapidly growing digital image usage. It has branched out many algorithms and adopted new techniques. Among them, feature fusion-based image classification methods rely on hand-crafted features traditionally. However, it has been proven that the bottleneck features extracted through pre-trained convolutional neural networks (C... View full abstract»

Here, a novel, yet simple, transform-based watermarking scheme for copyright protection has been proposed. The proposed method takes advantage of the rotation invariant property of the ripplet-II transform which makes the proposed method robust against rotation attacks. In the proposed method, firstly a cost function of perceptual transparency is formed in the ripplet-II domain. Secondly, the ridg... View full abstract»