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Differential box-counting (DBC) is one of the commonly used methods to estimate fractal dimension (FD) for gray scale images. It has been successfully applied in many applications such as image segmentation, pattern recognition, texture analysis and medical signal analysis. However, the accuracy improvement of FD estimation is still a grand challenge. This paper proposes a modified differential box-counting...
A novel multi-targets ISAR imaging method based on particle swarm optimization (PSO) and modified CLEAN technique is proposed in this paper. First, multi-targets are modeled as several separated group-targets in which translational motion of each target is analogous. And then, translational motion of each group-target is modeled as a polynomial, and the polynomial coefficient is estimated via PSO...
To provide tools for image understanding, non-trivial task of image segmentation is now put on a new semantic level of object detection. Internal, external and contextual region properties often can adequately represent image content but there arises field of view coverings. Truthful image interpretation strictly depends on valid number of regions. The goal is an attempt to solve image clustering...
Multiple Sclerosis (MS) is an auto-immune, inflammatory disease of the Central Nervous System (CNS), consisting in the progressive demyelinization of axonal fibers. Given its degenerative nature, MS treatment faces complex challenges for both pharmaceutical and therapeutic interventions. Indeed, patients with diagnostic of multiple sclerosis will require continuous rehabilitation for life in order...
Human vision can perceive object colors as being the same as colors under a white illuminant. However, images captured by a camera are influenced by the chromaticity of the illumination. Therefore, various illumination estimation algorithms have already been proposed for removing the chromaticity of illuminations in an image to improve the image quality. Most recently, NMFsc (nonnegative matrix factorization...
This paper proposes a novel depth map generation method using a pair of stereo images obtained from a single sensor. The proposed method generates a dense depth map as follows: i) sampling of the stereo image pair using photodiodes equipped with the black mask, ii) feature extraction in low light and noisy environment, iii) matching of the stereo images using motion estimation, and iv) matting of...
This paper proposes a hierarchical Bayesian model for estimating the parameters of asymmetric power distributions (APDs). These distributions are defined by shape, scale and asymmetry parameters which make them very flexible for approximating empirical distributions. A hybrid Markov chain Monte Carlo method is then studied to sample the unknown parameters of APDs. The generated samples can be used...
In apple harvesting robot, the first key part is the machine vision system. Identifying single objects from fruit images is the first and foremost task in machine vision system. However, the main problem affecting the identification of single fruits is that fruit regions in image taken in unstructured orchard environment are overlapping in some cases. On the basis of studies on fruit image segmentation...
A novel image segmentation algorithm based on a Bayesian framework is studied in this paper. We presents a new region and statistics based approach, which combines Voronoi tessellation technique and Maximum a posterior / Maximization of the posterior marginal (MAP /MPM) algorithm. The image domain is partitioned into a group of sub-regions by Voronoi tessellation, each of which is a component of homogeneous...
Recovering 3D depth from a single outdoor image is a basic problem in Computer Vision and Close-Range Photogrammetry. In this paper, an efficient depth estimation approach from a single outdoor image is presented. According to scene classification, depth of regions marked as sky, ground and vertical labels is respectively predicated. Firstly, a more accurate depth calculation model for ground regions...
A new region-based local stereo matching algorithm with accurate disparity estimation is proposed. For the local stereo matching, finding an appropriate support window is crucial to the performance of disparity estimation. In order to generate an accurate support region, a modified cross-based local approach combined with mean-shift segmentation is performed. We then further improve the reliability...
The spaceborne P-band synthetic aperture radar (SAR) is affected by ionospheric scintillation, which seriously impacts the imaging quality and measurements of biomass. Considering polarization modes and topographic features, a hybrid scheme for compensating ionospheric scintillation effect is proposed based on Phase Gradient Autofocus (PGA) and Faraday rotation (FR) estimation based method. Simulating...
This paper presents an approach for dense depth estimation taking the input of a trinocular stereo. The approach works with a global energy minimization framework based on Markov Random Field models. The occlusion and spatial consistency constraints are explicitly considered in an iterative fashion. Depth maps are initialized by belief propagation using AD-Census metric, and then refined by Mean Shift...
In this paper, a clothes segmentation method for fashion parsing is described. This method does not rely in a previous pose estimation but people segmentation. Therefore, novel and classic segmentation techniques have been considered and improved in order to achieve accurate people segmentation. Unlike other methods described in the literature, the output is the bounding box and the predominant color...
Frequent and more accurate water level measurement will allow for a more efficient distribution of water, resulting in less water loss. Therefore in this paper we propose a novel method for accurate water level detection and measurement applied on images of staff gauges, retrieved from mobile device camera. In the first step, we propose fast segmentation of the staff gauge using a 2-class random forest...
Lung cancer detection is one of the most important goals of medical diagnosis. To detect lung nodules usually classical X-ray and/or computed tomography (CT) images are used. The progression of the disease can be monitored if the doubling time of the volume of a pulmonary nodule is determined and followed, which means that the volume of a nodule has to be measured/estimated. To measure the nodule...
This paper proposes a foreground-based approach to generating a depth map which will be used for 2D-to-3D conversion. For a given input image, the proposed approach determines if the image is an object-view (OV) scene or a non-object-view (NOV) scene, depending on the existence of foreground objects which are clearly distinguishable from the background. If the input image is an OV scene, the proposed...
Image thresholding techniques are focused on quantitative estimation of cell confluence in microscopy imaging. Receiver operating characteristic (ROC) analysis is presented and discussed with application to uncertainty affecting cell confluence estimated by inspection of fluorescence micrographs.
In this paper we propose a novel method of estimating indoor scenes from a single full-view image. On the one hand, the conventional methods cope with limited field of view images, such as perspective images and hemispherical omnidirectional images, which result in visually open boundary condition, called open geometry. On the other hand, a full-view image results in a visually close boundary condition,...
We propose part-segment (PS) features for estimating an articulated pose in still images. The proposed PS feature evaluates the image likelihood of each body part (e.g. head, torso, and arms) robustly to background clutter and nuisance textures on the body and clothing. In contrast to similar segmentation features, part segmentation is improved by part-specific shape priors that are optimized by training...
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