Human matching between different fields of view is a difficult problem in intelligent video surveillance;whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it i...
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Scale space techniques have attracted much attention in the field of computer vision and imageprocessing. In particular, the curvature scale space (CSS) technique was selected in the MPEG-7 standard due to a number o...
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ISBN:
(纸本)9781424441990
Scale space techniques have attracted much attention in the field of computer vision and imageprocessing. In particular, the curvature scale space (CSS) technique was selected in the MPEG-7 standard due to a number of nice properties. In this paper the scale space concept is first explained in detail and its significance in solving shape-based vision problems is clarified. A brief survey of the theoretical developments of the CSS technique in the past few decades is then presented.
High precision identification of feature points is an important technology and one of the bases of computer vision, image analysis and imageprocessing. In the practical applications, the feature points can not be ide...
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ISBN:
(纸本)9781424441990
High precision identification of feature points is an important technology and one of the bases of computer vision, image analysis and imageprocessing. In the practical applications, the feature points can not be identified easily in various conditions of light illumination, visual angle, texture, and perspective projection. And in many cases, the size of feature point is small, the context is uncertain and the shape of feature point is different from each other. According to the properties of actual vision images, a novel method of feature point identification using multi-scale detecting technology is presented. In this thesis, an automatic circle feature point detection system is developed based on digital imageprocessing.techniques, in which, the feature points are detected in two scales. In large-scale recognition, the image pre-processing.is carried out to reduce the impact of image noise, and the feature points with various shape deformation can be found out. And then, the founded points are checked along with small scale detecting. The relationship of the points and their mappings in three dimensional space is obtained and used to judge if the point is a real feature point one by one. Thus the deformed feature points in various perspective projection conditions can be recognized correctly. Experimental results show that this approach for feature points identification is not only fast but also robust. The proposed technology is a kind of useful method for contour extraction and feature points identification in the fields of computer vision and image analysis.
Clinical histopathology is based on the analysis of immunohistochemistry (IHC) stained tissue images. Selection of antibodies for detecting the presence, type, and grade of cancerous tissue has a great influence on th...
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Clinical histopathology is based on the analysis of immunohistochemistry (IHC) stained tissue images. Selection of antibodies for detecting the presence, type, and grade of cancerous tissue has a great influence on the diagnostic potential of IHC tests. Automated evaluation methods for tissue microarrays applied to many combinations of antibody and tissue type can speed development of new clinical assays. We present an automatic method that successfully quantifies stain intensity, fraction of cells stained and sub-cellular location of staining in tissue microarray images. The method combines an opponent color preprocessor and a novel statistical approach for identifying brown and blue staining, followed by multilevel morphological processing. We verify the capability of our method by comparing the results to manually annotated image databases. We also demonstrate cross-tissue robustness using two clinical case study data.
The intensity-images captured by Time-of-Flight (ToF)-cameras are biased in several ways. The values differ significantly, depending on the integration time set within the camera and on the distance of the scene. Wher...
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ISBN:
(纸本)9781424423392
The intensity-images captured by Time-of-Flight (ToF)-cameras are biased in several ways. The values differ significantly, depending on the integration time set within the camera and on the distance of the scene. Whereas the integration time leads to an almost linear scaling of the whole image, the attenuation due to the distance is nonlinear resulting in higher intensities for objects closer to the camera. The background regions that are farther away contain comparably low values, leading to a bad contrast within the image. Another effect is that some kind of specularity may be observed due to uncommon reflecting conditions at some points within the scene. These three effects lead to intensity, images which exhibit significantly different values depending on the integration time of the camera and the distance to the scene, thus making parameterization of processing.steps like edge-detection, segmentation, registration and threshold computation a tedious task. Additionally, outliers with exceptionally high values lead to insufficient visualization results and problems in processing. In this work we propose scaling techniques which generate images whose intensities are independent of the integration time of the camera and the measured distance. Furthermore, a simple approach for reducing specularity effects is introduced.
With increasing technical advances, computer graphics are becoming more photorealistic. Therefore, it is important to develop methods for distinguishing between actual photographs from digital cameras and computer gen...
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ISBN:
(纸本)9781424423392
With increasing technical advances, computer graphics are becoming more photorealistic. Therefore, it is important to develop methods for distinguishing between actual photographs from digital cameras and computer generated images. We describe a novel approach to this problem. Rather than focusing on the statistical differences between the image textures, we recognize that images from digital cameras contain traces of resampling as a result of using a color filter array with demosaicing algorithms. We recognize that estimation of the actual demosaicing parameters is not necessary;rather, detection of the presence of demosaicing is the key. The in-camera processing.(rather than the image content) distinguishes the digital camera photographs from computer graphics. Our results show high reliability, on a standard test set of JPEG compressed images from con sumer digital cameras. Further we show the application of these ideas for accurately, localizing forged regions within digital camera images.
Segmentation of blood vessels and extraction of their centerlines in 3D angiography are essential to diagnosis and prognosis of vascular diseases, and advanced imageprocessing.and analysis. In this paper we propose a...
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ISBN:
(纸本)9781424423392
Segmentation of blood vessels and extraction of their centerlines in 3D angiography are essential to diagnosis and prognosis of vascular diseases, and advanced imageprocessing.and analysis. In this paper we propose a semiautomatic method to perform those two tasks simultaneously. A user supplies two end points to the algorithm and a vessel centerline between the two given points is extracted automatically. Local vessel widths are estimated as byproducts. Additional anchor points can be added in between to handle difficult situation. Our method is based upon a polygonal line algorithm. This algorithm is used to find principal curves, nonlinear generalization of principal components, from point clouds. We discuss an application of principal curve to vessel extraction from a theoretical viewpoint. A novel algorithm is then proposed for the application. No data interpolation is needed in the algorithm and centerlines extracted are adaptive to the vasculature complexity on account of their nonparametric representation. We have tested the method on two synthetic data sets and two clinical data sets. Results show that it has high robustness to variation in image resolution, voxel anisotropy and noise. Moreover centerlines obtained are in subvoxel precision and local widths estimated are accurate under limit of image resolution.
Real-time pose estimation of a free-hand Ultrasound (US) image without any position sensor is desirable for diagnostics and image guidance, but it suffers from poor image quality as a result of processing. The paper c...
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ISBN:
(纸本)9781424423392
Real-time pose estimation of a free-hand Ultrasound (US) image without any position sensor is desirable for diagnostics and image guidance, but it suffers from poor image quality as a result of processing. The paper confronts this problem by proposing a new 6-DOF pose estimation method based on a fast registration process making use of 3D implicit polynomials (IP). The proposed registration method has some main advantages over the traditional methods. First, our formulation is based on minimization of energy functional derived from IP gradient flow, and thus it is more efficient than traditional registration because it eliminates the cost for calculating point-wise correspondences. Second, the efficient calculation benefits from the property of IP having few coefficients, which means that both the gradient field and its transformation can be calculated in air extremely light manner Third, applying a real-time US image pose estimation, we demonstrate the capabilities of overcoming the limitations of unconstrained freehand US data, resulting in robust and fast pose estimation.
In this paper a biometric system for personal identification, realized through the manipulation of retinal fundus images and the detection of its bifurcation points, is described. In the image pre-processing.step, a s...
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ISBN:
(纸本)9783540859833
In this paper a biometric system for personal identification, realized through the manipulation of retinal fundus images and the detection of its bifurcation points, is described. In the image pre-processing.step, a strong contrast exaltation between blood vessels and the background in retinal image is carried out;then blood vessels are extracted and next the vasculature bifurcation and crossover points are identified within squared shaped regions used to window the image. Finally the features sets are compared with a patternrecognition algorithm and a novel formulation is introduced to evaluate a similarity score and to obtain the personal identification.
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagno...
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ISBN:
(纸本)9781424418145
B-scan ultrasound is the primary means for the diagnosis of fatty liver. However, due to use of various ultrasound equipments, poor quality of ultrasonic images and physical differences of patients, fatty liver diagnosis is mainly qualitative, and often depends on the subjective judgment of technicians and doctors. Therefore, computer-aided feature extraction and quantitative analysis of liver B-scan ultrasonic images will help to improve clinical diagnostic accuracy, repeatability and efficiency, and could provide a measure for severity of hepatic steatosis. This paper proposed a novel method of fatty liver diagnosis based on liver B-mode ultrasonic images using support vector machine (SVM). Fatty liver diagnosis was transformed into a patternrecognition problem of liver ultrasound image features. According to the different characteristics of fatty liver and healthy liver, important image features were extracted and selected to distinguish between the two categories. These features could be represented by near-field light-spot density, near-far-field grayscale ratio, grayscale co-occurrence matrix, and neighborhood gray-tone difference matrix (NGTDM). A SVM classifier was modeled and trained using the clinical ultrasound images of both fatty liver and normal liver. It was then exploited to classify normal and fatty livers, achieving a high recognition rate. The diagnostic results are satisfactorily consistent with those made by doctors. This method could be used for computer-aided diagnosis of fatty liver, and help doctors identify the fatty liver ultrasonic images rapidly, objectively and accurately.
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