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This paper presents a method to construct the measurable aerial panorama based on panoramic image and multi-view oblique images matching. It's a new way that the visual expression of three-dimensional geographical environment is provided by stitching multi-view UAV images into aerial panorama images, which is widely used in smart city, smart travel, safety emergency and many other fields. The problem...
Variational image segmentation based on the Mumford-Shah model requires to solve the heat diffusion equations in evolving irregular subdomains. It brings about significant difficulties in efficient and accurate segmentation, especially, in multi-phase scenarios. In this paper, we propose a new Mumford-Shah type model involving a smoothing operator, acting a similar role as the diffusion process and...
In this paper, we present a novel learning framework for traversable region detection. Firstly, we construct features from the super-pixel level which can reduce the computational cost compared to pixel level. Multi-scale super-pixels are extracted to give consideration to both outline and detail information. Then we classify the multiple-scale super-pixels and merge the labels in pixel level. Meanwhile,...
It is one of the primary responsibilities of any department of diagnostic radiology to minimize the amount of unnecessary radiation administered to patients during diagnostic procedure. In this paper, we present three effective ways of quantifying the information content of computed radiography (CR) images for radiation dose optimization through shape and wavelet analyses. The experimental results...
In this paper, we proposed a new method (CSR+OSD) for the extraction of irregular open prostate boundaries in noisy extracorporeal ultrasound image. First, cascaded shape regression (CSR) is used to locate the position of prostate boundary in the images. In CSR, a sequence of random fern predictors are trained in a boosted regression manner, using shape-indexed features to achieve invariance against...
This paper presents a new approach for human hair length detection. In contrast to others, the proposed method is able to segment hairs from different views of human heads even with low resolution. Faces are not necessary to be visible in the images, as no face detection is needed in our method. Firstly, it conducts background subtraction to detect foreground objects and then detects human heads with...
A level set method is proposed for flame front detection and curvature calculation on turbulent premixed OH Planar Laser Induced Fluorescence (OH-PLIF) images. The Flame front on an OH-PLIF image is detected by our proposed curve evolution model. In this model, a global term is designed to make the evolution curve converge to the flame front and a Gaussian kernel function is used to detect the flame...
In this paper, we propose a novel method for object localization, generally applicable to medical images in which the objects can be distinguished from the background mainly based on feature differences. We design a new CRF model with additional contrast and interest-region potentials, which encode the higher-order contextual information between regions, on the global and structural levels. We also...
In this paper, shadow detection and compensation are treated as image enhancement tasks. The principal components analysis (PCA) and luminance based multi-scale Retinex (LMSR) algorithm are explored to detect and compensate shadow in high resolution satellite image. PCA provides orthogonally channels, thus allow the color to remain stable despite the modification of luminance. Firstly, the PCA transform...
In studying the relationship between risk factors and breast cancer, the growth patterns of fat pads and glandular tissues are considered as important biomarkers. The aim of this study is to measure the growth pattern statistics of rat mammary pads and glandular tissues with magnetic resonance (MR) time sequence images. In this paper, we proposed methods containing sequential steps to extract and...
In this paper, we present a modified deterministic annealing algorithm, which is called DA-RS, for robust image segmentation. The presented algorithm is implemented by incorporating the local spatial information and a robust non-Euclidean distance measure into the formulation of the standard deterministic annealing (DA) algorithm. This implementation offers several improved features compared to existing...
In studying the relationship between risk factors and breast cancer, growth patterns of the fat pads and glandular tissues are important features. The goal of this small animal study is to measure the size of mammary pads over the time. To achieve this goal, we propose a hierarchical approach to segmenting out rat body, mammary fat pads and evaluating their development in Tl weighted magnetic resonance...
Moving object segmentation is an important task in vision-based traffic monitoring applications. In traffic scenes, various outliers such as sudden illumination changes, moving cast shadows, camera jitter, etc., often cause serious errors in image analysis due to misclassiflcation of moving objects. An efficient moving object refining approach is thus expected. In this paper, we address the problem...
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