Measuring the similarity between articulated shapes is a fundamental yet challenging problem. This paper proposes a novel shape descriptor based on Width Distributions (WD), which is robust to articulations. We show t...
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Measuring the similarity between articulated shapes is a fundamental yet challenging problem. This paper proposes a novel shape descriptor based on Width Distributions (WD), which is robust to articulations. We show that the width distributions are articulation insensitive yet descriptive to distinguish different shapes with varied part structures. With measurements on distributions only, the proposed method does not require any alignment between two objects and thus is more robust than correspondence-based measurements. First, the medial axes of the objects are extracted and fitted to B-Splines to remove outliners. The width of the object shape perpendicular to the medial axis can be calculated for each position on the medial axis. The histograms of those widths are compared using chi-square method for similarity. Experiments on standard 2D shape database show that the proposed method performed better than standard shape distribution algorithms and similarly to other articulation-robust shape descriptors, such as inner-distance. The speed of the proposed method is much faster than the more sophisticated inner-distance, as the proposed method is much simpler in nature and requires limited imageprocessing and pattern classification. These results suggested it could be an efficient and effective method to describe and to match articulated shapes.
This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving im...
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Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper pre...
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Lung nodules from low dose CT (LDCT) scans may be used for early detection of lung cancer. However, these nodules vary in size, shape, texture, location, and may suffer from occlusion within the tissue. This paper presents an approach for segmentation of lung nodules detected by a prior step. First, regions around the detected nodules are segmented; using automatic seed point placement levels sets. The outline of the nodule region is further improved using the curvature characteristics of the segmentation boundary. We illustrate the effectiveness of this method for automatic segmentation of the Juxta-pleural nodules.
This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving im...
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This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving images has its basis in solving a set of non-linear equations of thin-plate splines. The regularized bending energy of the thin-plate splines along with the localization error of established correspondences is jointly minimized with the fixed and transformed image difference, where, the transformed image is represented by the set of non-linear equations defined over the moving image. The traditional thin-plate splines with established correspondences may provide good registration of the anatomical targets inside the prostate but may fail to provide improved contour registration. On the contrary, the proposed framework maintains the accuracy of registration in terms of overlap due to the non-linear thin-plate spline functions while also producing smooth deformations of the anatomical structures inside the prostate as a result of established corrspondences. The registration accuracies of the proposed method are evaluated in 20 pairs of prostate mid-gland ultrasound and magnetic resonance images in terms of Dice similarity coefficient with an average of 0.982 ± 0.004, average 95% Hausdorff distance of 1.54 ± 0.46 mm and mean target registration and target localization errors of 1.90±1.27 mm and 0.15 ± 0.12 mm respectively.
Automatic suitable-matching area selection is an important research in visual guidance, scene matching and local non-texture target tracking. Meanwhile, it is the major research subject in computervision and accurate...
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Surface colour changes and specular reflections are two major problems in 3D modelling using shape-from-shading (SFS). This paper proposes to pre-process the input image for a typical SFS algorithm, so that the result...
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A softproofing system is required to faithfully display color images. As the user relies on an appropriate calibration of the system, a method for the evaluation of the quality of the calibration is required. Such a m...
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ISBN:
(纸本)9781617388897
A softproofing system is required to faithfully display color images. As the user relies on an appropriate calibration of the system, a method for the evaluation of the quality of the calibration is required. Such a method has recently been developed and allows a critical side-by-side comparison between the original sample and the reproduced monitor image by placing the original directly in front of the monitor. An internal light source of the softproofing system establishes an almost uniform illumination of the target. In this paper, we present a method to spatially equalize the brightness of the monitor with respect to an object placed in front of the monitor. The automatic calibration procedure requires minimal user intervention and utilizes a standard RGB camera in combination with a special calibration target. The results show that the camera enables an accurate and uncomplicated homog-enization of the monitor with respect to the object in front of the monitor.
Surface colour changes and specular reflections are two major problems in 3D modelling using shape-from-shading (SFS). This paper proposes to pre-process the input image for a typical SFS algorithm, so that the result...
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Surface colour changes and specular reflections are two major problems in 3D modelling using shape-from-shading (SFS). This paper proposes to pre-process the input image for a typical SFS algorithm, so that the resultant image has no colour changes and specular reflection. First, a chromaticity-based specular reflection removal algorithm is applied to achieve a pure diffuse (Lambertian) reflected image. Then, a novel chromaticity-based colour adjustment approach is proposed to generate an image without surface colour changes. The standard SFS algorithms can then be applied successfully onto the processed images to produce plausible 3D models. In experiments, the proposed approach was tested on standard SFS datasets with complex surface colours. The experimental results show it's promising to facilitate SFS algorithms to handle SFS problems with more complex surface properties and illumination conditions.
Background subtraction is widely used for extracting unusual motion of object of interest in video images. In this paper, we propose a fast and flexible approach of object detection based on an adaptive background sub...
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Background subtraction is widely used for extracting unusual motion of object of interest in video images. In this paper, we propose a fast and flexible approach of object detection based on an adaptive background subtraction technique that also effectively eliminates shadows based on color constancy principle in RGB color space. This approach can be used for both outdoor and indoor environments. Our proposed method of background subtraction makes use of multiple thresholding technique for detecting object of interests for any given scene. Once the moving object has been detected from the complex background, then the shadows are detected and eliminated by considering some environmental parameters.
Abdominal aortic aneurysm is a cardiovascular disease which occurs due to an abnormal weakening of the aorta wall. This failure in aortic wall causes the inner layer to be ruptured because of excessive blood pressure....
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Abdominal aortic aneurysm is a cardiovascular disease which occurs due to an abnormal weakening of the aorta wall. This failure in aortic wall causes the inner layer to be ruptured because of excessive blood pressure. Consequently, the blood flows into the space between lumen and epithelial, hence a thrombus is generated. On the other hand, excessive growth in the aorta diameter can lead to death as a result of a rupture in the epithelial. In this paper, we present a technique for automatic segmentation of abdominal aortic aneurysm. The proposed method integrates the exclusive information extracted from histogram and morphological properties of aortic lumen to segment the aorta. Then the proposed algorithm utilizes a search technique with priori information about the lumen to segment epithelial area automatically.
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