A well-defined three-dimensional (3-D) reconstruction of bone-cartilage transitional structures is crucial for the osteochondral restoration. This paper presents an accurate, computationally efficient and fully-automa...
A well-defined three-dimensional (3-D) reconstruction of bone-cartilage transitional structures is crucial for the osteochondral restoration. This paper presents an accurate, computationally efficient and fully-automated algorithm for the alignment and segmentation of two-dimensional (2-D) serial to construct the 3-D model of bone-cartilage transitional structures. Entire system includes the following five components: (1) image harvest, (2) image registration, (3) image segmentation, (4) 3-D reconstruction and visualization, and (5) evaluation. A computer program was developed in the environment of Matlab for the automatic alignment and segmentation of serial sections. Automatic alignment algorithm based on the position's cross-correlation of the anatomical characteristic feature points of two sequential sections. A method combining an automatic segmentation and an image threshold processing was applied to capture the regions and structures of interest. SEM micrograph and 3-D model reconstructed directly in digital microscope were used to evaluate the reliability and accuracy of this strategy. The morphology of 3-D model constructed by serial sections is consistent with the results of SEM micrograph and 3-D model of digital microscope.
Software fault prediction techniques are helpful in developing dependable software. In this paper, we proposed a novel framework that integrates testing and prediction process for unit testing prediction. Because high...
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Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looki...
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ISBN:
(纸本)9781467301732
Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looking infrared (DLIR) image sequences in this paper. A complete model of the proposed method is designed firstly and the principles of some key technologies are introduced as following. Perspective transformation is used to solve the projective problems of landmark translation, rotation and scale variance in real-time image sequence. The size of landmark is estimated real-timely by using flight parameters and imaging parameters for getting the model with an appropriate scale. Based on the matching results of landmark and flight parameters, target position technology is proposed to identify the position of target by using the position relation between landmark and target. Experimental results using real-world image data with complicated background showed that the proposed method not only causes high precisely locating results, but also has good robustness for target occlusion.
Recently, asymmetric 3D-2D face recognition has been paid increasing attention. It enrolls in textured 3D faces and performs identification using only 2D facial images, therefore it generally achieves a better result ...
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Recently, asymmetric 3D-2D face recognition has been paid increasing attention. It enrolls in textured 3D faces and performs identification using only 2D facial images, therefore it generally achieves a better result than 2D algorithms do, and avoids inconvenience of data acquisition and computation of 3D methods as well. In this paper, a biological vision-based facial representation, namely Oriented Gradient Maps (OGMs), is introduced for such an application. It simulates the response of complex neurons to gradient information within a pre-defined neighborhood, and thus can describe local texture changes of 2D faces and local geometry variations of 3D faces at the same time. Due to its property of being highly distinctive, these OGMs improve accuracies of both matching steps of asymmetric face recognition, i.e. (1) 3D-2D matching using Canonical Correlation Analysis (CCA); (2) 2D-2D matching using LBP histogram based features and Sparse Representation Classifier (SRC). Some comparative experiments are carried out on the complete FRGC v2.0 database, and the achieved results clearly highlight the effectiveness of the biological vision-based facial description and its successful application to asymmetric face recognition.
image annotation is the process of assigning proper keywords to describe the content of a given image, which can be regarded as a problem of multi-object image classification. In this paper, a general multi-label anno...
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Recently, a new representation for recognizing instances and categories of scenes called spatial Principal component analysis of Census Transform histograms (PACT) has shown its excellent performance in the scene imag...
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In Epilepsy EEG signal classification, the main time-frequency features can be extracted by using sparse representation with marching pursuit (MP) algorithm. However, the computational burden is so heavy that it is al...
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In Epilepsy EEG signal classification, the main time-frequency features can be extracted by using sparse representation with marching pursuit (MP) algorithm. However, the computational burden is so heavy that it is almost impossible to apply MP to real time signal processing. To reduce complexity of sparse representation, we propose to adopt harmony search method in searching the best atoms. Because harmony search method can find the best atoms in continuous time-frequency dictionary, the performance of epilepsy EEG signal classification is enhanced. The validity of this method is proved by experimental results.
We present the design and fabrication of metamaterials, and investigated the power transmission properties of the metamaterials in the frequency ranging from 1.04THz to 4.25THz. The measured results reveal a global ma...
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Aiming at the effective approximation of sampling particle set relative to system state in observation uncertainty, a novel cost reference particle filter based on adaptive particle swarm optimization is proposed. In ...
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The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, w...
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