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.
For a robot to operate efficiently in a human centered environment, it should be able to interact and learn unknown objects autonomously. Such capabilities will enable a robot to enrich its internal knowledge of the environment without human assistance. However, a crucial limitation of robots is their inability to comprehend representations of novel objects without priors. Human efforts are required...
Just noticeable difference (JND), which reveals the visibility of our human visual system (HVS), is useful for image/video coding. Due to the content complexity, it is hard to accurately estimate the JND thresholds for different image blocks (e.g., edge and texture). Research on cognitive science indicates that the HVS is adaptive to extract the visual regularities for scene perception and understanding...
We propose a fusion method for high dynamic range (HDR) imaging based on the estimated camera response function (CRF) and fused gradients from input multi-exposure images. We introduce an objective function consisting of data fidelity and gradient-based constraint functions, and HDR images are produced via minimizing it. These functions are respectively defined based on the estimated CRF and the fused...
This paper proposes a gaze estimation algorithm using 3-D eyeball model and eyelid shape. The gaze estimation suffers from differences of eye shapes and individual behaviors, and requires user-specific gaze calibration. The proposed method exploits the usual 3-D eyeball model and shapes of the eyelid to estimate gaze without user-specific calibration and learning. Since the gaze is closely related...
A coarse-to-fine horizon detection method based on between-class variance is present. Firstly, the original image is resized to a smaller one and plenty of straight lines are selected acoording to two line parameters which are distance to image center and inclination angle in the resized image. A criterion based on the between-class variance is set up for determining the best straight line which is...
In this paper the elimination of image distortion and subsequent estimation of intrinsic camera parameters, while extracting the real object dimensions from photographs is presented. Research analysis includes description of the basic concepts related to the camera calibration. Following the analysis, the most suitable calibration method has been chosen and implemented as a software solution. The...
In this paper, we present a fast approach for matching stereo images acquired by a stereo sensor embedded in a moving vehicle. The proposed approach exploits the disparity map already computed at the preceding frame to improve the matching results at the current one. An edge association method is used to track the edge curves over time. Local disparity constraints are computed for all the edge points...
Dermoscopy images usually suffer from spatially-varying defocus blur, which will easily influence the lesion analysis result and lead to wrong aided diagnosis. In this paper, a novel blind deblurring framework is proposed for dermoscopy images with spatially-varying defocus blur. The defocus map is firstly estimated by support vector regressor (SVR) learning model using the natural scene statistics...
Noise in medical images may affect the result of clinical diagnosis. We propose a rapid noise variances estimation method named Gabor Wavelet Laplacian convolution (GWLC). This method allows rapid estimation of image noise variance without complex calculation. We exclude unwanted image edge lines through Gabor wavelet transform edge detection. Henceforth, we can estimate the noise variance of the...
Corners are salient features in two dimensional images. Compared to other approaches, contour-based corner detectors have been reported to be more effective. We analysed two state-of-the-art contour-based corner detectors, Chord-to-Point Distance Accumulation (CPDA) and very recently developed Curve to Chord Ratio (CCR). Both of these detectors use multiple parameters which are manually or experimentally...
In this paper we present a new lane markers detection and estimation algorithm aiming to improve lane detection methods. We first estimate the area of lane marking using the profile of the lane estimation in a confidence map. After that a fitting method is applied to improve the lane marker detection accuracy. To track our lane markers over time and make the association between two iteration, we use...
Mammography is the main imaging technique for breast cancer diagnosis and prevention. Many image processing techniques though require the breast region to be adequately defined in order to provide reliable results. Pectoral muscle segmentation is one of the most challenging tasks in this domain since the limits between the muscle and the actual breast region are sometimes quite difficult to distinguish...
Community detection is a valuable tool for analyzing and understanding the structure of complex networks. This work investigates the application of the density-based algorithm DBSCAN* to the community detection problem. Given, though, that this algorithm requires a lower bound for the community size to be determined a priori, this work proposes the application of a Martingale process to DBSCAN* so...
Magnetic resonance imaging provides a superior soft tissue contrast and a noninvasive means for automatic diagnosis of tissue pathogenesis. However, like most imaging modalities, it suffers from a compromise between the achievable spatial resolution, scan time efficiency, and signal-to-noise-ratio. To address this difficulty, super-resolution techniques have been proposed to enhance the spatial resolution...
A novel approach for noise reduction in Magnetic Resonance Image field is proposed. The methodology adopts a Maximum A Posteriori estimator and exploits Markov Random Field theory for adapting the filter to the local nature of the image. Differently from other widely adopted filters, the proposed algorithm works in the complex domain, i.e., real and imaginary components of the acquired images are...
Robust estimation of linear structures such as edges and junction features in digital images is an important problem. In this paper, we use an adaptive robust structure tensor (ARST) method where the local adaptation process uses spatially varying adaptive Gaussian kernel that is initialized using the total least-squares structure tensor solution. An iterative scheme is designed with size, orientation,...
The restoration of motion-blurred image is one of important subjects of image restoration. This paper mainly researched on the restoration methods for motion-blurred image based on estimated motion blurring angle and motion blurring length. First, the motion blurring angle is estimated by Hough transform algorithm. In order to reduce the impact of concrete structure on the detection, the edge detection...
In order to reconstruct the all-in-focus image from a conventional camera, a spatially-varying defocus deblurring approach based on blur map and TV/L2 regularization was proposed. Firstly, lenticular defocus model was studied and analyzed, and the principle, characteristic and applicability of disk defocus model and Gaussian defocus model were generalized; Secondly, we modified the local contrast...
This paper introduces a fast blind deconvolution strategy for image deblurring by modifying a recent natural image model, i.e., the total generalized variation (TGV), which aims at reconstructing an image with higher-order smoothness as well as sharp edges. But, when it turns to the blind issue, as demonstrated either empirically or theoretically by a few previous blind deblurring works, natural image...
Nowadays the estimation of crowd density and people counting is a great focus under public security affairs in surveillance. A scheme for crowd counting estimation based on linear regression function is proposed in this paper. In the proposed scheme, the Light Effect Suppression Model (LESM), which effectively reduces the sensitivity to illumination change, is applied to extract the foreground. Besides...
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.