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Structural similarity index (SSIM) considers the loss of structural information as a degradation of quality. Structure of original and distorted images are compared by using low order moments, which are mean, variance and correlation. In this paper, we extend the SSIM by incorporating shape parameters of distributions, which are the higher order moments based skewness and kurtosis. We show that skewness...
Identifying the consumption patterns of electric customers and grouping them to classes according to their load characteristics can be very meaningful for power supply and demand side management in smart grid. Previously, tariff structures are mainly based on the type of activity. However, the type of activity and electrical behavior of the customer have poor relationship. Using clustering techniques...
This paper presents an automatic heart murmur detection and delineation algorithm. Multiple cardiac cycles with murmurs are processed in two steps. In the first step, the first and second heart sounds are detected and identified to label cardiac cycles as the first heart sound (S1), followed by a systole period, the second heart sound (S2), a diastole period, and then repeated with S1 and the rest...
Recovery of sparse signals with unknown clustering pattern in the case of having partial erroneous prior knowledge on the supports of the signal is considered. In this case, we provide a modified sparse Bayesian learning model to incorporate prior knowledge and simultaneously learn the unknown clustering pattern. For this purpose, we add one more layer to support-aided sparse Bayesian learning algorithm...
This paper proposes a saliency detection approach using multi-mapping based on global-local structural information. Firstly, a global-background-suppression(GBS) image and a Lab color space hybrid(CSH) image are obtained through different mapping rules. Secondly, both of them are segmented several times to produce multiple shape images. Thirdly, the above shape images are multiplied with GBS image...
Existing Ml-reference image quality assessment models first compute a full image quality-predictive feature map followed by a spatial pooling scheme, thereby producing a single quality score. Here we study spatial sampling strategies that can be used to more efficiently compute reliable picture quality scores. We develop a random sampling scheme on single scale full-reference image quality assessment...
Despite its proven accuracy and computational efficiency, the Natural Element Method (NEM) suffers from the lack of a well-suited numerical integration technique. In this work different integration approaches are applied and tested on the NEM framework. Comparative analyses in terms of accuracy and computational cost are presented. The goal here is to elucidate the impact of these techniques on the...
A challenge in meshless methods dealing with vector electromagnetic problems is to produce numerical solutions that are free of spurious modes given that the generated vector field does not satisfy the condition of zero divergence. The edge meshless method constructs its approximations using specials shape functions based on edges to produce vector fields that are divergence free and to guarantee...
Tree architecture plasticity enables individuals to maximize filling of the available space and minimize the competition effect; tree crowns can be distributed more regularly than stem bases. We conducted a study in a temperate mixed forest (Krakow, Poland) to test the idea of a new angular competition index (CI) and its application in modeling crown radii (CR) and crown projections (CPs) of 30 Quercus...
The representation of a magnetic material using the Preisach Model of hysteresis requires the determination of the Everett function through the measurement of a complete set of B-H curves. Unfortunately, this data is not available in the literature for most materials, which can be a limitation for practical engineering applications. In this paper, we propose an identification procedure of the Everett...
The paper introduces a novel model-guided method for liver segmentation in CT and PET-CT images. Using a model liver volume as a template and a liver shape annotated in one of the patient slices, it automatically segments the whole liver volume in the patient dataset. The method is based on non-deformable registration of the model volume to the patient data and combination of components pre-segmented...
This paper proposes the novel method which detect circles in an image by an approach of the template matching, not an approach of the Circle Hough Transform(CHT) voting edge points to the parameter space. The approach such as the Hough transform needs huge computing cost and huge memory. Furthermore, a lot of false circles are detected in a complicated background. In order to overcome these problems,...
Understanding how people read technical, business, and medical documents can help businesses and doctors better communicate with employees, patients, and consumers. This paper seeks to build on the research of Shieh, C., and Hosei, B., as well as Pichert, J. W., & Elam, P., into usability testing of language in technical, business, and medical documents. This paper also seeks to add to the discussion...
Robust and accurate visual tracking is needed for many computer vision applications from video summarization to visual surveillance. Visual tracking remains to be a challenging task because of factors such as changing object appearance, illumination variations and shadows, partial and full occlusions, camera motion, distractors, and scale changes. Recently our group proposed a Likelihood of Features...
The max-tree is a mathematical morphology data structure that represents an image through the hierarchical relationship of connected components resulting from different thresholds. It was proposed in 1998 by Salembier et al., since then,many efficient algorithms to build and process it were proposed.There are also efficient algorithms to extract size, shape and contrast attributes of the max-tree...
In shape learning for a digital image, it is a common that one would encountered two major problems, which are noise and missing edges. The existing research approaches aim to reduce noise, while at the same time to recover the missing edges. However, noise reductions using contour detector or smoothening techniques could indirectly distort the salient boundary. Most of the research works only focus...
In this paper, the objective evaluation of the performance of multi-sensor cooperative detection is studied. A new method to evaluate the performance of multi-sensor cooperative detection is proposed based on the object's geometric shape. The method utilizes the property that extend fractal characteristic of target is sensitive to the size and contrast of the target, searching for the fractal characteristics...
Recently, the 3D mesh segmentation is considered as an important stage in many applications in 3D shape analysis. In fact, extensive research has been performed to offer multiple approaches and algorithms for 3D mesh segmentation. Nevertheless, it is relatively hard to assess which algorithm produces more accurate segmentation quality than the other. Various methods have been proposed to evaluate...
It is widely recognized that the segmentation of 3D objects is one of the most important disciplines in computer vision. In the last few years, developments of 3D segmentation techniques are in continual expansion. However, little work has been directed toward the evaluation of 3D mesh segmentation methods and consequently there is still no satisfactory performance measure. In this paper, a new evaluation...
This paper presents a novel pose-indexed based multi-view (PIMV) face alignment framework. Most of the current cascaded regression face alignment methods generally start with a mean shape. However, when the initial shape is far from the ground truth, the performance significantly deteriorates. Our approach aims to obtain a preferable initial shape from a pose-indexed shape searching space. This space...
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