In digital image forensics, camera model identification seeks for the source camera model information from the given images under investigation. To achieve this goal, one of the popular approaches is extracting from t...
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Biometrics is a measurement of a person's physical and behavioral characteristics. Iris image is one of many biometrics data such as fingerprint, voice, face, and gait that can be used as an identifier. Iris is th...
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The identification of traditional Chinese medicine is the key to control the quality of traditional Chinese medicine and ensure the safety and effectiveness of clinical medication. Compared with the physical and chemi...
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ISBN:
(纸本)9781665477260
The identification of traditional Chinese medicine is the key to control the quality of traditional Chinese medicine and ensure the safety and effectiveness of clinical medication. Compared with the physical and chemical identification methods with expensive equipment and complex operation, microscopic image identification of traditional Chinese medicine is an effective method with low cost. However, this method still has a high learning cost and identification errors due to staff fatigue. Therefore, this paper designs an effective automatic recognition approach of Chinese herbal medicine by micro imageprocessing. The core of this method is the introduction of transfer learning and data enhancement methods, which effectively alleviates the problem of insufficient number of microscopic image data samples in the microscopic recognition of traditional Chinese medicine, and realizes the automatic recognition of traditional Chinese medicine. We construct a library of microscopic recognition features of Chinese herbal medicine, and designe evaluation experiments on this basis. The results show that the recognition performance of our method is better than that of SSD method, especially the F1 value is increased by 7.25 %.
image classification is one among the significant tasks that can benefit industry through advancement in science and technology. Texture images possess a specific pattern that can be utilized to uniquely identify a te...
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In agriculture, environmental science, and land resource management, soil analysis is crucial. The ability to extract detailed data from soil images has recently become possible thanks to the integration of image proc...
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In this paper, we propose a new model-based method for estimating face pose from a facial image. In this method, computer generated models are used for reducing the cost of collecting the images of various models. By ...
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In this paper, we propose a new model-based method for estimating face pose from a facial image. In this method, computer generated models are used for reducing the cost of collecting the images of various models. By the use of computer generated models, it is very easy to change the acquisition conditions of the model images, such as illumination and pose of the object. Additionally, the eigen space technique is employed for reducing the huge capacity of the prepared models and huge computation for matching input images with model images. We show the results of pose estimation from facial images of varying illumination for demonstrating the effectiveness of the proposed method.
In this paper, an image-based method is presented for fall detection using statistical human posture sequence modeling. Specifically, a series of laboratory simulated falls and activities of daily living (ADLs) are pe...
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ISBN:
(纸本)9780769550893
In this paper, an image-based method is presented for fall detection using statistical human posture sequence modeling. Specifically, a series of laboratory simulated falls and activities of daily living (ADLs) are performed and recorded by a Kinect sensor as training video data. The skeleton view of a human body in these video recordings is extracted using the Kinect for Windows SDK. Hidden Markov Models are used for modeling the fall posture sequences and distinguishing different fall activities and ADLs. Our experimental results demonstrate an average fall recognition rate above 80% and the capability of early warning for falls.
Retinal image analysis is employed to automate screening process through low-level feature extraction and classification. Supervised classification approaches are dependent on kernels or distance metrics to handle com...
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ISBN:
(纸本)9781450352437
Retinal image analysis is employed to automate screening process through low-level feature extraction and classification. Supervised classification approaches are dependent on kernels or distance metrics to handle complex manifolds as they warp feature space for effective classification with less complex boundaries between classes. Proposed approach identifies control points (Voronoi diagram) by exploring the structures of class specific manifolds which constructs complex boundaries with piecewise linear nature. Such a framework has less number of hyperparameters to tweak resulting easy control and understanding of the system. The learning characteristics of the proposed algorithm has been depicted on toy and optical coherence tomography data set. It has illustrated effective performance in identification of retinal pathologies and compared against off-the-shelf classifiers with various parameters. Proposed algorithm is capable of accommodating unsupervised approaches other than Fuzzy C-Means reflecting its adaptability.
Multi-spectral linage Fusion is a new research field in imageprocessing. In this paper, for achieving a better fusion result, a image fusion method based on the intensity;-hue-saturation(IHS) Transform and Bidimensio...
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ISBN:
(纸本)9781424410651
Multi-spectral linage Fusion is a new research field in imageprocessing. In this paper, for achieving a better fusion result, a image fusion method based on the intensity;-hue-saturation(IHS) Transform and Bidimensional Empirical Mode Decomposition(BEMD) is proposed. Firstly, the multi-spectral image is transformed into IHS component. Secondly, the histogram-matched panchromatic image and intensity component are decomposed into a set of BIMFs respectively by means of BEMD. Thirdly, the new intensity component can be obtained by merging the BIMFs of histogrant-matched panchromatic image and intensity component. Finally, the new intensity, hue, and saturation components are transformed back to RGB. Experimental results show that this new method can preserve the spectral information it? the fusion image;meanwhile, it can merge the spatial details of the panchromatic image.
The project aims to address the escalating challenge of malware, a critical threat in the cybersecurity domain. Traditional detection methods are struggling to keep pace with sophisticated, evolving malware attacks. D...
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