We present in this paper the realization of a classification board, for real-time image segmentation. The classification of each pixel is completed using a real time extraction of attributs and a geometric classificat...
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ISBN:
(纸本)0818679204
We present in this paper the realization of a classification board, for real-time image segmentation. The classification of each pixel is completed using a real time extraction of attributs and a geometric classification method by stress polytope training, which ensures a high decision speed (100 ns per pixels) and good performances. The decision operator has been integrated in the form of a full custom circuit, and the extraction of parameters is performed using a single high density FPGA.
The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neuralnetworks and imageprocessing. This research i...
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ISBN:
(纸本)0819424927
The recognition of human faces is a phenomenon that has been mastered by the human visual system and that has been researched extensively in the domain of computer neuralnetworks and imageprocessing. This research is involved in the study of neuralnetworks and wavelet imageprocessing techniques in the application of human face recognition. The objective of the system is to acquire a digitized still image of a human face, carry out pre-processing on the image as required, an then, given a prior database of images of possible individuals, be able to recognize the individual in the image. The pre-processing segment of the system includes several procedures, namely image compression, denoising, and feature extraction. The imageprocessing is carried out using Daubechies wavelets. Once the images have been passed through the wavelet-based image processor they can be efficiently analyzed by means of a neural network. A back- propagation neural network is used for the recognition segment of the system. The main constraints of the system is with regard to the characteristics of the images being processed. The system should be able to carry out effective recognition of the human faces irrespective of the individual's facial-expression, presence of extraneous objects such as head-gear or spectacles, and face/head orientation. A potential application of this face recognition system would be as a secondary verification method in an automated teller machine.
The proceedings contains 68 papers from the Conference of SPIE - applications of Digital imageprocessing XX. Topics discussed include: urban texture analysis;texture analysis for wooden plate classification;restorati...
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The proceedings contains 68 papers from the Conference of SPIE - applications of Digital imageprocessing XX. Topics discussed include: urban texture analysis;texture analysis for wooden plate classification;restoration of motion-blurred images;logical wavelets;color restoration for astronomical applications;and automated galaxy classification using artificialneuralnetworks.
A hierarchical structure of neuralnetworks has been constructed and utilized for fast identification of images. applications include recognition and extraction of partially obscured objects. The networks are self-org...
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ISBN:
(纸本)0819405787
A hierarchical structure of neuralnetworks has been constructed and utilized for fast identification of images. applications include recognition and extraction of partially obscured objects. The networks are self-organizing. The selection and registration of necessary templates are automated at all levels. Training of the networks takes a minimal amount of time. The development is mostly carried out on a Sun-3 workstation, VAX and IRIS 4D/240 computers with a single processor. However, this algorithm is more effective if implemented in parallel computers. A preliminary parallel implementation study with an AMT DAP-610 systolic array computer was conducted and favorable results obtained. The experimentation of the algorithm with various image data with or without partial occlusion shows robustness of the networks. Further applications of the networks are in progress.
Edge detection can be treated as a problem in optimization - a problem that can be solved with a Hopfield neural network. This paper describes a neural-network based model capable of producing high-quality edge imagery.
ISBN:
(纸本)0819421413
Edge detection can be treated as a problem in optimization - a problem that can be solved with a Hopfield neural network. This paper describes a neural-network based model capable of producing high-quality edge imagery.
In this paper a method that facilitates an iconic query of an image/video database is presented. A query object is characterised by colour and texture properties. The same characteristics are computed locally far the ...
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ISBN:
(纸本)0818679204
In this paper a method that facilitates an iconic query of an image/video database is presented. A query object is characterised by colour and texture properties. The same characteristics are computed locally far the database images. A statistical decision rule is then used to test for similarity between the iconically specified query and the database image descriptors. We show that by carefully selecting the set of descriptors the false alarm rate can be significantly reduced. The floating search feature selection method has been adapted to make it applicable to the hypothesis testing based query processing. The dimensionality reduction not only improves the performance but also enhances the computational efficiency of the method.
Coherent imagery emerges as one of the major domains in imageprocessing and includes topics as diversified as radar, medical and surface analysis. Whatever the application, the resulting image is noisy corrupted. In ...
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ISBN:
(纸本)0818679204
Coherent imagery emerges as one of the major domains in imageprocessing and includes topics as diversified as radar, medical and surface analysis. Whatever the application, the resulting image is noisy corrupted. In coherent imaging, images suffer from speckle noise [1], whose main characteristic is to be multiplicative. The proposed method takes explicitly into account the multiplicative property of the noise while preserving discontinuities in the restored image. Moreover, ina second step our algorithm estimates the noise, thus the information contained in the speckle still remains usable.
The technology using artificial intelligence (AI) allows, through the preprocessing of video and image data, their transformation into traffic information, the recognition in abusive conditions of elements, the specif...
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ISBN:
(纸本)9783031686498;9783031686504
The technology using artificial intelligence (AI) allows, through the preprocessing of video and image data, their transformation into traffic information, the recognition in abusive conditions of elements, the specification of the different characteristics of the vehicle (type, brand, model, color), object detection and tracking, automatic calibration and positioning. Algorithms for performance evaluation can evaluate recognition quality and detect malfunctions due to external factors, reduced lighting conditions, or incorrect camera installation. This article discusses the application of AI and deep learning techniques to identify vehicle wheels. It highlights the preprocessing of image and video data to extract traffic information, detect vehicle attributes, and perform object tracking. The study focuses on understanding AI and convolutional neuralnetworks (CNNs) for imageprocessing, emphasizing the significance of feature extraction algorithms. The research outlines the methodology for creating a dataset of annotated wheel images, selecting the YOLO detection algorithm, and using the Darknet Github framework for training and testing CNNs. It discusses the training process, including configuration, data augmentation, and evaluation metrics like Mean Average Precision (MAP) and Intersection Over Union (IOU). Finally, the article concludes with insights into the practical applications of the developed wheel detection system, suggesting future improvements and potential integrations with other projects.
A new efficient image coding scheme, based on Quadtree Representation and Block Entropy Coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated ...
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ISBN:
(纸本)0818679204
A new efficient image coding scheme, based on Quadtree Representation and Block Entropy Coding (QRBEC), for encoding the wavelet transform coefficients of images is presented. The property of HVS is also incorporated into the quantization process. In addition, how to flexibly control the quantization level as well as output bitrate of the coder is also investigated. The coding efficiency of the coder is quite competitive with the well-known EZW coder, and requires less computation burden. The proposed coding scheme can also be applied in image sequence coding, resulting in satisfactory performance.
For high compression ratios current video coding standards produce noticeable blocking and ringing noise due to a rigid block structure and coarse quantization. We propose a new method for reduction of these coding ar...
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ISBN:
(纸本)0818679204
For high compression ratios current video coding standards produce noticeable blocking and ringing noise due to a rigid block structure and coarse quantization. We propose a new method for reduction of these coding artifacts based on spatially adaptive constrained least squares restoration. The proposal is numerically simple and yields visually convincing results for intra as well as inter coded images. As post-processing technique it is compatible to all existing image and video coding standards.
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