this paper proposes a new methodology for micro pattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial c...
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this paper proposes a new methodology for micro pattern analysis in digital images based on fuzzy numbers. A micro-pattern is the structure of the gray-level pixels within a neighborhood and can describe the spatial context of the image, such as edge, line, spot, blob, corner, texture, and more complex patterns. By treating a pixel neighborhood as a fuzzy set and each pixel gray-level as a fuzzy number, we can evaluate the membership degree of the central pixel to the others. We have called this method the Local Fuzzy Pattern (LFP). Using a sigmoid membership function, we proved that the proposed methodology surpasses the Hit-rate of the Local Binary Pattern (LBP), for texture classification. the LFP proved to be robust to image rotation. Moreover, our proposed formulation for the LFP is a generalization of previously published techniques, such as Texture Unit, LBP, FUNED, and Census Transform.
Image segmentation is still a challenging issue in pattern recognition. Among the various segmentation approaches are those based on graph partitioning, which present some drawbacks, one being high processing times. W...
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Image segmentation is still a challenging issue in pattern recognition. Among the various segmentation approaches are those based on graph partitioning, which present some drawbacks, one being high processing times. Withthe recent developments on complex networks theory, pattern recognition techniques based on graphs have improved considerably. the identification of cluster of vertices can be considered a process of community identification according to complex networks theory. Since data clustering is related with image segmentation, image segmentation can also be approached via complex networks. However, image segmentation based on complex networks poses a fundamental limitation which is the excessive numbers of nodes in the network. this paper presents a complex network approach for large image segmentation that is both accurate and fast. To that, we incorporate the concept of super pixels, to reduce the number of nodes in the network. We evaluate our method for both synthetic and real images. Results show that our method can outperform other graph-based methods both in accuracy and processing times.
Bias field (in homogeneity) correction and skull stripping are initial standard procedures in medical image analysis of the human brain. Several works have investigated the effects of prior in homogeneity correction o...
Bias field (in homogeneity) correction and skull stripping are initial standard procedures in medical image analysis of the human brain. Several works have investigated the effects of prior in homogeneity correction on skull stripping using 1.5 Tesla magnetic resonance (MR) images, but this question remains unanswered for higher magnetic fields. this paper fills this gap using 3 Tesla MR-images, by proposing a novel alternate sequence of skull stripping, morphological operations, in homogeneity correction and intensity standardization, withthe first at the beginning and end of the sequence, denominated Iterative Skull Stripping methodology. Conversely to what happens in 1.5T images, experimental evaluation shows that, in 3 Tesla datasets, in homogeneity effect plays an important role in stripping the brain. this observation produces a deep impact on previous and future studies that rely on skull stripping operation.
Kinect is a device introduced in November 2010 as an accessory of Xbox 360. the acquired data has different and complementary natures, combining geometry with visual attributes. For this reason, Kinect is a flexible t...
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Kinect is a device introduced in November 2010 as an accessory of Xbox 360. the acquired data has different and complementary natures, combining geometry with visual attributes. For this reason, Kinect is a flexible tool that can be used in applications from several areas such as: Computer graphics, Image Processing, Computer Vision and Human-Machine Interaction. In this way, the Kinect is a widely used device in industry (games, robotics, theater performers, natural interfaces, etc.) and in research. We will initially present some concepts about the device: the architecture and the sensor. We then will discuss about the data acquisition process: capturing, representation and filtering. Capturing process consists of obtaining a colored image (RGB) and performing a depth measurement (D), with structured light technique. this data is represented by a structure called RGBD Image. We will also talk about the main tools available for developing applications on various platforms. Furthermore, we will discuss some recent projects based on RGBD images. In particular, those related to Object Recognition, 3D Reconstruction, Augmented Reality, Image Processing, Robotic, and Interaction. In this survey, we will show some research developed by the academic community and some projects developed for the industry. We intend to show the basic principles to begin developing applications using Kinect, and present some projects developed at the VISGRAF Lab. And finally, we intend to discuss the new possibilities, challenges and trends raised by Kinect.
In this paper, we present a simple and fast inverse halftoning algorithm, targeted at reconstructing halftoned images generated using dispersed-dot ordered dithering algorithms. the proposed algorithm uses a simple se...
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We propose a memory-efficient method that computes persistent homology for 3D gray-scale images. the basic idea is to compute the persistence of the induced Morse-Smale complex. Since in practice this complex is much ...
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the detection of QR codes, a type of 2D barcode, as described in the literature consists merely in the determination of the boundaries of the symbol region in images obtained withthe specific intent of highlighting t...
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Estimating human pose in static images is a challenging task due to the high dimensional state space, presence of image clutter and ambiguities of image observations. In this paper we propose a method to automatically...
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