检索结果-内蒙古大学图书馆

M-channel nonlinear phase filter banks in image compression:: Structure, design, and signal extension

ieee TRANSACTIONS ON signal processing 2007年第4期55卷 1339-1351页

作者： Uto, Toshiyuki Oka, Tomohiro Ikehara, Masaaki Ehime Univ Dept Comp Sci Fac Engn Matsuyama Ehime 790 Japan Keio Univ Dept Elect & Elect Engn Fac Sci & Technol Tokyo 108 Japan

This paper describes a transform coding technique based on M-channel perfect reconstruction filter banks with a nonlinear phase. In contrast with linear-phase filter banks, the nonlinearity provides an extra degree of freedom that can be used to design a more efficient transform. We present new lattice structures of paraunitary and perfect reconstruction (biorthogonal) filter banks, which can be implemented with a lower computational complexity and/or represented by a few free parameters, through the decomposition of the lattice blocks and the displacement across the delay block. We further discuss a smooth extension method for nonlinear-phase filter banks to obtain a nonexpansive transform. The promise of our proposed approaches is demonstrated through several design examples, extended signals and compression results.

关键词： image coding lattice structure nonlinear phase filter bank nonexpansive decomposition

来源：评论

学校读者我要写书评

暂无评论

Non-pixel Robot Stereo

Non-pixel Robot Stereo

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Tyler C. Folsom University of British Columbia Vancouver BC Canada

The 2005 DARPA Grand Challenge was a 213 Km robot race across the Mojave Desert between Nevada and California. Our team attempted to run the course using only stereo vision. I designed a novel real-time large-image stereo vision system that uses sparse stereo and is biologically inspired. It uses a filter similar to that used in primary visual cortex to locate small line segments. These are then arranged to form a polyline representation of the scene and estimate the depth. The technique was capable of nine frames per second of a megapixel image on a single processor. Accuracy was questionable and the robot did not compete in the race for other reasons

关键词： Gabor filters Biology computing Stereo vision Intelligent robots signal processing algorithms image edge detection Retina Polynomials computational intelligence Biomedical signal processing

来源：评论

学校读者我要写书评

暂无评论

Finding behaviour patterns along highways by image processing

Finding behaviour patterns along highways by image processin...

引用

8th International symposium of Hungarian Researchers on computational intelligence and Informatics, CINTI 2007

作者： Max, Gyula Department of Automatization and Applied Informatics Budapest University of Technology and Economics Po. Box. 91 H-1521 Budapest Hungary

We spend more and more time on travelling. Travelling by metro or tram gives us almost certain time to get home. And what about is travelling by car? Many persons travel hours to go working or to get home. In rush time the main roads and highways are full of cars. Can we simulate drivers' behaviour and their decision making process? This paper tries to find patterns in drivers' behaviour and simulate these processes.

关键词： image processing

来源：评论

学校读者我要写书评

暂无评论

Application of computation intelligence techniques for energy load and price forecast in some states of USA

Application of computation intelligence techniques for energ...

引用

ieee International symposium on Intelligent signal processing

作者： Mourao, Joao C. Ruano, Antonio E. Univ Algarve Fac Sci & Technol Ctr Intelligent Syst P-8005139 Faro Portugal

ISBN: (纸本)9781424408290

The purpose of this paper is to forecast the load and the price of electricity, 49 hours ahead. To accomplish these goals. computational intelligence techniques were used, specifically artificial neural networks and genetic algorithms. The neural networks employed are RBFs (Radial Basis Functions), fully connected and with just one hidden layer. The genetic algorithm used was MOGA (Multiple Objective Genetic Algorithm), which, as the name indicates, minimizes not a single objective but several. The neural networks are trained for one step ahead, and Its output is feedback until 49 hours are calculated. MOGA is used for the input selection and for topology determination. The data used was kindly given by the University of Auburn, USA, and refers to real data from some North-American states.

关键词： load and price forecast genetic algorithms neural networks

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Face Clustering using SIFT image Features

Hierarchical Face Clustering using SIFT Image Features

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Panagiotis Antonopoulos Nikos Nikolaidis Ioannis Pitas Department of Informatics Aristotle University of Thessaloniki Thessaloniki Greece

In this paper an algorithm to cluster face images found in video sequences is proposed. A novel method for creating a dissimilarity matrix using SIFT image features is introduced. This dissimilarity matrix is used as an input in a hierarchical average linkage clustering algorithm, which yields the clustering result. Three well known clustering validity measures are provided to asses the quality of the resulting clustering, namely the F measure, the overall entropy (OE) and the Gamma statistic. The final result is found to be quite robust to significant scale, pose and illumination variations, encountered in facial images

关键词： Face detection Clustering algorithms Humans Hidden Markov models signal processing algorithms Video sequences Face recognition Couplings Clustering methods Testing

来源：评论

学校读者我要写书评

暂无评论

A multi-layer neural network and an adaptive linear combiner for on-line harmonic tracking

A multi-layer neural network and an adaptive linear combiner...

引用

ieee International symposium on Intelligent signal processing

作者： Zouidi, Abdelaziz Fnaiech, Farhat AL-Haddad, Kamal Univ Tunis Ecole Super Sci & Tech Tunis Equipe Rech Signal Image & Commande Intelligent S 5 Av Taha Hussein Tunis 1008 Tunisia CRC ECPE Ecole Technol Super Quebec City PQ H3C 1K3 Canada

ISBN: (纸本)9781424408290

Intelligent techniques of harmonic detection or estimation are nowadays of a great interest in power system applications, their ability to deal with high non-linearities attract researchers to investigate the performance of these methods mainly based on artificial intelligence namely using artificial neural networks. In the literature many harmonic detection or estimation methods were presented, in this paper we focus on a new idea to apply an adaptive linear neuron (ADALINE) and a multi-layer artificial neural net work (M-LANN) [5] to estimate the fundamental component and the total harmonic content of a distorted signal.

关键词： harmonic detection artificial intelligence artificial neural networks

来源：评论

学校读者我要写书评

暂无评论

Application of Opposition-Based Reinforcement Learning in image Segmentation

Application of Opposition-Based Reinforcement Learning in Im...

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Farhang Sahba Hamid R. Tizhoosh Magdy M. M. A. Salama University of Waterloo Waterloo ON CA Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

In this paper a method for image segmentation using an opposition-based reinforcement learning scheme is introduced. We use this agent-based approach to optimally find the appropriate local values and segment the object. The agent uses an image and its manually segmented version and takes some actions to change the environment (the quality of segmented image). The agent is provided with a scalar reinforcement signal as reward/punishment. The agent uses this information to explore/exploit the solution space. The values obtained can be used as valuable knowledge to fill the Q-matrix. The results demonstrate potential for applying this new method in the field of medical image segmentation

关键词： Learning image segmentation signal processing Application software computational intelligence System analysis and design Design engineering Systems engineering and theory Pattern analysis Machine intelligence

来源：评论

学校读者我要写书评

暂无评论

Opposition-Based Window Memoization for Morphological Algorithms

Opposition-Based Window Memoization for Morphological Algori...

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Farzad Khalvati Hamid R. Tizhoosh Mark D. Aagaard Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada

In this paper we combine window memoization, a performance optimization technique for image processing, with opposition-based learning, a new learning scheme where the opposite of data under study is also considered in solving a problem. Window memoization combines memoization techniques from software and hardware with the repetitive nature of image data to reduce the number of calculations required for an image processing algorithm. We applied window memoization and opposition-based learning to a morphological edge detector and found that a large portion of the calculations performed on pixels neighborhoods can be skipped and instead, previously calculated results can be reused. The typical speedup for window memoization was 1.42. Combining window memoization with opposition-based learning yielded a typical increase of 5% in speedups

关键词： image processing signal processing algorithms Optimization Hardware image edge detection Application software computational intelligence Design engineering Systems engineering and theory Software algorithms

来源：评论

学校读者我要写书评

暂无评论

On improved MRI segmentation using hierarchical computational intelligence techniques and textural analysis of the discrete wavelet transform domain

On improved MRI segmentation using hierarchical computationa...

引用

ieee International symposium on Intelligent signal processing

作者： Karras, D. A. Hellin Open Univ Automat Dept Chalkis Inst Technol Athens 16342 Greece

ISBN: (纸本)9781424408290

This paper investigates a novel feature extraction approach to MRI segmentation based on identifying the critical image edges by using textural (cooccurrence matrices) analysis of the Discrete Wavelet Transform (DWT) domain. Furthermore, the presented approach is based on formulating the problem as a two-stage unsupervised classification task using a modified Kohonen's Self Organizing Feature. Map (SOFM) along with Independent Component Analysis (ICA). The main goal of such a research effort is to better identify abrupt textural image changes without increasing the presence of noise in the resulting image. The suggested methodology is based on novel discrete wavelet descriptors involving the discrete k-level 2-D wavelet transform and cooccurrence matrices analysis applied to sliding windows raster scanning the original image. The proposed two-stage classification scheme applied to such textural wavelet descriptors and using a modified Vector Quantizing Self-Organizing Feature Map (SOFM) and ICA analysis is compared with a corresponding two-stage scheme involving PCA analysis and tire widely used SOFM, trained with Kohonen 's algorithm. The feasibility of this novel two-stage proposed approach is studied by applying it to the edge structure segmentation problem of brain slice MRI images. The promising results presented in the experimental study illustrate a performance favourably compared, also, to that of traditional Sobel edge detectors supported by usual contour tracing methods.

关键词： texture descriptors DWT descriptors MRI segmentation edge detection ICA PCA two-stage classifiers neural networks DWT unsupervised learning SOFM

来源：评论

学校读者我要写书评

暂无评论

A Multi-Window Stereo Vision Algorithm With Improved Performance at Object Borders

A Multi-Window Stereo Vision Algorithm With Improved Perform...

引用

ieee symposium on computational intelligence in image and signal processing, ciisp

作者： Jun Zhao Jayantha Katupitiya ARC Centre of Excellence for Autonomous Systems University of New South Wales Sydney NSW Australia

Conventional correlation based stereo vision algorithms have poor performance at object borders due to occlusion. In this paper, a new matching sequence has been introduced. To detect left object border, a left shifted window is used with right image as the reference image and process from left to right. This method gives excellent left object border detection while detection of right object border is poor. The right object borders can be detected with equal success using a right shifted window with left image as reference and process from right to left. The combination result is good detection at both object borders

关键词： Stereo vision Object detection signal processing algorithms Pixel computational intelligence Manufacturing processes Australia Performance evaluation Testing Shape

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：