The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Nowadays it is extremely easy to tamper with images and share them thanks to social media. Identifying the transformation history is imperative to be able to trust these images. We address this problem by using image phylogeny trees, where the root is the image that has been less tampered with and as every generation is obtained from the transformation of its parents, the leaves are the most transformed...
Grabcut, an iterative algorithm based on Graph Cut, is a popular foreground segmentation method. However, it suffers from a main drawback: a manual interaction is required in order to start segmenting the image. In this paper, four different methods based on image pairs are used to obtain an initial extraction of the foreground. Then, the obtained initial estimation of the foreground is used as input...
Recent studies validated the feasibility of estimating heart rate from human faces in RGB video. However, test subjects are often recorded under controlled conditions, as illumination variations significantly affect the RGB-based heart rate estimation accuracy. Intel newly-announced low-cost RealSense 3D (RGBD) camera is becoming ubiquitous in laptops and mobile devices starting this year, opening...
Acquiring the light transport (LT) of a scene is important for various applications such as radiometric analysis, image-based relighting, and controlling appearance of the scene. The multispectral LT, i.e. the LT in multiple primary colors enables us not only to enhance the color gamut but also to investigate wavelength-dependent interactions between light and a scene. In this paper, we propose a...
Retinal pathologies that are detected too late and/or left untreated can seriously damage eyesight. It is important to monitor the retina and react to any pathological changes. A fast, accurate, non-invasive, and even three-dimensional retina examination is the optical coherence tomography (OCT). In this paper we propose a new automated classification method for evaluation of vitreomacular interface...
The k-nearest-neighbour classifiers (k-NN) have been one of the simplest yet most effective approaches to instance based learning problem for image classification. However, with the growth of the size of image datasets and the number of dimensions of image descriptors, popularity of k-NNs has decreased due to their significant storage requirements and computational costs. In this paper we propose...
HEVC (high efficiency video coding), as the latest video coding standard, is more efficient than H.264/AVC, nevertheless it also brings in a very high computational complexity. To reduce the time of CU (coding unit) splitting or PU (prediction unit) mode deciding, a fast algorithm based on ANN (artificial neural network) and texture analysis is proposed in this paper. First, we acquire and then label...
Recently, computer-aided celiac disease diagnosis has been promoted to provide an objective opinion besides histological examination of biopsies and visual assessment of macroscopic mucosal tissue. State-of-the-art techniques, however, are not accurate enough to provide incentive for clinical deployment. In this work, we answer two questions: Do computers and human experts make similar classification...
Super resolution (SR) algorithms are widely used in forensics investigations to enhance the resolution of images captured by surveillance cameras. Such algorithms usually use a common interpolation algorithm to generate an initial guess for the desired high resolution (HR) image. This initial guess is usually tuned through different methods, like learning-based or fusion-based methods, to converge...
In Optical Camera Communication systems an important issue is the spatial intersymbol interference (blurred images) that can arise when Multi-Input Multi-Output techniques are applied. However, the transmitted symbols are described with very high resolution, due to the high number of pixels composing the camera. To take advantage of this characteristic, in this paper we use a semiblind spatial fractionally-spaced...
This paper proposes an improved histogram-based approach to identifying whether an image is never compressed or has undergone JPEG compression with quality factor 100. The key idea is that the image's DCT (Discrete Cosine Transform) coefficients follow either of two families of parametric distributions, corresponding respectively to never compressed images and JPEG-100 compressed ones. This paper...
Gesture recognition is one of the important tasks for human System Interaction (HRI). This paper describes a novel approach intended to recognize 3D dynamic composed gestures by combining Dynamic Time Warping (DTW) with an Adaptive Sliding Window which the name Adaptive Dynamic Time Warping (ADTW). We use the skeleton algorithm provided by the Kinect SDK to track the upper part of body and extract...
Binarized statistical image features (BSIF) represents a general purpose texture descriptor originally designed for texture description and classification, such as local binary patterns (LBP) or local phase quantisation (LPQ). Recently, BSIF has extensively been applied for the purpose of biometric recognition, for instance based on face or palmprint images. While recognition accuracy reported for...
Digital pathology employs images that were acquired by imaging thin tissue samples through a microscope. The preparation of a sample from a biopt to the glass slide entering the imaging device is done manually introducing large variability in the samples to be imaged. For visible contrast it is necessary to stain the samples prior to imaging. Different stains attach to different compounds elucidating...
Image quality measurements are valuable tools, crucial for most image processing applications, and used in particular to assess and compare the image restoration (IR) quality. The objective of this work is to investigate the potential of such measures when used as cost functions (integrated in the global criterion) to enhance the restoration performance. In this paper, the proposed approach uses the...
Fully automated detection and localisation of fruit in orchards are key components in creating automated robotic harvesting systems. During recent years a lot of research on this topic has been performed, either using basic computer vision techniques, like colour based segmentation, or by resorting to other sensors, like LWIR, hyperspectral or 3D. Recent advances in computer vision present a broad...
In the field of biometrics and forensics, age estimation is an important topic, for example when determining the age of human subjects or when assessing the age of a particular taken biometric sample or captured forensic trace from crime scenes. The latter case is investigated in this paper, with the focus on latent fingerprints. Here, the trace age represents the time between deposition and capture...
Sonar imaging is currently the exemplary choice used in underwater imaging. However, since sound signals are absorbed by water, an image acquired by a sonar will have gradient illumination; thus, underwater maps will be difficult to process. In this work, we investigated this phenomenon with the objective to propose methods to normalize the images with regard to illumination. We propose to use MIxed...
Deep learning is a rather new approach to machine learning that has achieved remarkable results in a large number of different image processing applications. Lately, application of deep learning to detect and classify spectral and spatio-spectral signatures in hyperspectral images has emerged. The high dimensionality of hyperspectral images and the limited amount of labelled training data makes deep...
Single image super-resolution (SR) reconstruction aims to estimate a noise-free and blur-free high resolution image from a single blurred and noisy lower resolution observation. Most existing SR reconstruction methods assume that noise in the image is white Gaussian. Noise resulting from photon counting devices, as commonly used in image acquisition, is, however, better modelled with a mixed Poisson-Gaussian...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.