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Hippocampal shrinkage is a main biomarker for the detection of Alzheimer's disease and Temporal lobe Epilepsy (TLE). Mostly, developing methods for the hippocampus segmentation are unable to initialize automatically due to its low contrast boundary and uncertain position with respect to the wide range of human brain size. This paper will describe how to reduce the search area in brain MRI to determine...
Cortical Thickness (CTh) estimation from Magnetic Resonance Imaging (MRI) data of Multiple Sclerosis (MS) patients is biased at variable extent by the presence of white matter lesions. To overcome this limitation, several methods have been developed. In this study, we evaluate the impact on CTh measurements of different lesion corrections obtained combining three lesion segmentations (manual or automatic)...
Image procession algorithms for compensation of scattered radiation influence in X-ray imaging were proposed, studied and optimized by numerical simulations. The algorithms include scattering estimation by convolution (superposition) technique, estimation of kernel functions by Monte-Carlo (MC) simulations, determination the optimal number and shape of kernel functions and images segmentation. Determination...
In this work we address the problem of blind deblurring using a single space-variantly defocused image containing text. We estimate both the all-in-focus image and the blur map corresponding to the space-variant point spread function of the finite aperture camera. Since this problem is highly ill-posed we exploit a recently proposed technique [1] to obtain an initial estimate of the space-variant...
Schizophrenia (SZ) is a neurological disorder, which affects linguistic, memory, consciousness and executive functions of the brain. Magnetic resonance imaging (MRI) is used to capture structural abnormalities in human brain regions. In this work, segmentation of ventricle region from Schizophrenic MR brain images was carried out using optimized energy minimization framework. The images considered...
In this paper, we address the problem of detecting and segmenting partial image blur from a single input image. Instead of assuming particular image priors or requiring additional user annotation, we propose a novel learning framework which jointly solves the tasks of blur kernel estimation and image blur segmentation, so that partial image blur can be automatically separated from the remaining parts...
This paper presents a very simple and efficient algorithm to estimate 1, 2 or 3 orthogonal vanishing point(s) on a calibrated image in Manhattan world. Unlike the traditional methods which apply 1, 3, 4, or 6 line(s) to generate vanishing point hypotheses, we propose to use 2 lines to get the first vanishing point v1, then uniformly take sample of the second vanishing point v2 on the great circle...
The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work is to implement and evaluate a complete multistixel estimation pipeline on an embedded, energy-efficient, GPU-accelerated device. This work presents a full GPUaccelerated implementation of stixel estimation that produces...
In most cases image distortions modelled by convolution and additive white noise have unknown model parameters, such as convolution kernel (point spread function — PSF) and noise power. Different methods of blind deconvolution which iteratively approximate PSF use some initial kernel estimation; their performance is sufficiently dependent on the precision of that estimate. Modelling initial PSF as...
Depth estimation and spatial awareness given a single monocular image is a challenging task for a computer as depth information is not retained when the 3D world is projected onto a 2D plane. Therefore, we must combine our prior knowledge with other monocular cues present in the image, such as occlusion, texture variations, and shadows to understand the depth of the image. In this paper, we present...
The seed germination test is an important process for successful farming. This process is time-consumed and needed to be done by an expert. In this paper, the image processing method is applied to measure a germination rate. The proposed method used a digital camera to capture the rice image, the root and seed sections are segmented using the HSV color model. The seed that has root attached is considered...
Lung segmentation in chest radiographs is a requisite pre-processing step in the Computer-aided Diagnosis (CAD) system for the detection of chest diseases. This paper proposes an unsupervised lung segmentation method in chest radiographs based on shadow filter and multilevel thresholding. The method consists of three main processes: pre-processing, initial lung field estimation and noise elimination...
In this paper, we propose a new approach for dense disparity estimation in a global energy minimization framework. We combine the feature matching cost defined using the learned hierarchical features of given left and right stereo images, with the pixel-based intensity matching cost to form the data term. The features are learned in an unsupervised way using the deep deconvolutional network. Our regularization...
High dynamic range (HDR) imaging is highly demanded in computer vision algorithms. An HDR image is composed with several low dynamic range (LDR) images, which usually have some disparities. In many HDR imaging algorithms, the disparities are estimated based on the texture information of the LDR images. However, the texture information is often lost completely if scenes include extremely bright and...
When a planar structure is observed from multiple views, the projections of its corresponding 3D points on each image are related by a homography. Its estimation is a key step in many computer vision tasks where either the rigid motion between views or a per-pixel image correspondence is sought. The vast majority of multi-view homography estimation techniques relies on matching a sparse set of point-to-point...
Warping-based image stitching methods often suffer from perspective variations among multiple images and lead to shape and perspective distortions in stitching results. Moreover, they also quickly lose their efficiency in low-textured images, due to the lack of reliable point correspondences. To solve these problems, this paper presents a locally warping-based image stitching by imposing line constraints...
We propose a novel superpixel extraction method named USEQ to generate regular and compact superpixels. To reduce the computational burden of iterative optimization procedures used in most recent approaches, the spatial and color quantizations are performed in advance to represent pixels and superpixels. Maximum a posteriori estimation in both pixel and region levels is then adopted to aggregate pixels...
In order to fast register a camera into a 3D scene model under the Manhattan-World assumption, a method of matching corresponding 2D and 3D lines based on vanishing point is proposed in this paper. Firstly, this method detects line segments and estimates three orthogonal vanishing points to determine the local length of camera and the matrix from world to camera space. Afterwards, one line is drawn...
This paper proposes a real-time hand finger motion capturing method using Kinect. It consists of three modules: hand region segmentation, feature points extraction, and joint angle estimation. The first module extracts the hand region from the depth image. The second module applies a pixel classifier to segment the hand region into eight characteristic sub-regions and the residual sub-region. The...
Languages such as Chinese and Japanese have a significantly large number (several thousands) of alphabets as compared to other languages, and each of their sentences consists of several concatenated words with wide varieties of inflected forms; thus appropriate word segmentation is quite difficult. Therefore, recently proposed sophisticated language-processing methods designed for languages such as...
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