472 Result(s)
within
Image Processing and Computer Vision
Yi**ang Chen
Chapter
Conference Paper
-
Chapter and Conference Paper
Interactive Display of 3D Medical Objects
Interactive display of internal human organs has recently received much attention because of its potential applications. Capabilities for visualization, manipulation and quantitation are the common requirement...
-
Chapter and Conference Paper
Face recognition using a face-only database: A new approach
In this paper, a coarse-to-fine, LDA-based face recognition system is proposed. Through careful implementation, we found that the databases adopted by two state-of-the-art face recognition systems[1,2] were in...
-
Chapter and Conference Paper
Hierarchical segmentation and representation with dynamic link architecture neural network
A segmentation scheme based on tracing objects through scale space is proposed. For analyzing the image structure in scale space, a hierarchical neuraloscillator network is proposed. Its intrinsic dynamics pro...
-
Chapter and Conference Paper
Multiscale image representation and edge detection
In this paper, we present an edge detection method based on the thin-plate spline with tension. Under regularization theory, the image is represented in a convolution form between the original image data and a...
-
Chapter and Conference Paper
A Simple Implementation of the Stochastic Discrimination for Pattern Recognition
The method of stochastic discrimination (SD) introduced by Kleinberg ([6,7]) is a new method in pattern recognition. It works by producing weak classifiers and then combining them via the Central Limit Theorem to...
-
Chapter and Conference Paper
Gravity-Center Template Based Human Face Feature Detection
This paper presents a simple and fast technique for geometrical feature detection of several human face organs such as eyes and mouth. Human face gravity-center template is firstly used for face location, from...
-
Chapter and Conference Paper
Averaging Weak Classifiers
We present a learning algorithm for two-class pattern recognition. It is based on combining a large number of weak classifiers. The weak classifiers are produced independently with diversity. And they are comb...
-
Chapter and Conference Paper
The Lower and Upper Approximations of Fuzzy Sets in a Fuzzy Group
In this paper we define the lower and upper approximations of fuzzy sets in a group with respect to a fuzzy normal subgroup and study their product properties. We introduce the notion of a rough fuzzy subgroup...
-
Chapter and Conference Paper
Segmentation of Left Ventricle via Level Set Method Based on Enriched Speed Term
Level set methods have been widely employed in medical image segmentation, and the construction of speed function is vital to segmentation results. In this paper, two ideas for enriching the speed function in ...
-
Chapter and Conference Paper
Benchmarking of Fingerprint Sensors
At present, there are many competing fingerprint sensors available. Thus, fingerprint sensor benchmarking is necessary but unfortunately no proper methodology is available. This paper attempts to address this ...
-
Chapter and Conference Paper
Vision-Based Sign Language Recognition Using Sign-Wise Tied Mixture HMM
In this paper, a new sign-wise tied mixture HMM (SWTM-HMM) is proposed and applied in vision-based sign language recognition (SLR). In the SWTMHMM, the mixture densities of the same sign model are tied so that...
-
Chapter and Conference Paper
A New ART Neural Networks for Remote Sensing Image Classification
A new ART2A-C algorithm based on fuzzy operators to cluster the remote sensing images and aerials is proposed in this paper. By combining two ART ANNs with higher performance, the traditional ART2A-C is develo...
-
Chapter and Conference Paper
Performance Improvement of Vector Quantization by Using Threshold
Vector quantization (VQ) is an elementary technique for image compression. However, the complexity of searching the nearest codeword in a codebook is time-consuming. In this work, we improve the performance of...
-
Chapter and Conference Paper
Robust and Adaptive Backstep** Control for Nonlinear Systems Using Fuzzy Logic Systems
In this note, a robust adaptive tracking control problem is discussed for a class of affine nonlinear systems in the strict-feedback form with unknown nonlinearities. A unified and systematic procedure is deve...
-
Chapter and Conference Paper
A Sampling-Based Method for Mining Frequent Patterns from Databases
Mining frequent item sets (frequent patterns) in transaction databases is a well known problem in data mining research. This work proposes a sampling-based method to find frequent patterns. The proposed method...
-
Chapter and Conference Paper
Validation and Comparison of Microscopic Car-Following Models Using Bei**g Traffic Flow Data
In this oppaper, camera calibration and video tracking technology are used to get the vehicle location information so as to calibrate the Gazis-Herman-Rothery (GHR) model and fuzzy car-following model. The det...
-
Chapter and Conference Paper
Adaptive Neural Network Control for Multi-fingered Robot Hand Manipulation in the Constrained Environment
This note presents a robust adaptive neural network (NN) control scheme for multi-fingered robot hand manipulation system in the constrained environment to achieve arbitrarily small motion and force tracking e...
-
Chapter and Conference Paper
Feature Extraction for Handwritten Chinese Character by Weighted Dynamic Mesh Based on Nonlinear Normalization
This paper describes a new feature extraction method contributing to improvement of the performance of a handwritten Chinese character recognition system. By using enhanced weighted dynamic meshes based on non...
-
Chapter and Conference Paper
Classification of Chromosome Sequences with Entropy Kernel and LKPLS Algorithm
Kernel methods such as support vector machines have been used extensively for various classification tasks. In this paper, we describe an entropy based string kernel and a novel logistic kernel partial least s...
-
Chapter and Conference Paper
Self-organized Locally Linear Embedding for Nonlinear Dimensionality Reduction
Locally Linear Embedding (LLE) is an efficient nonlinear algorithm for map** high-dimensional data to a low-dimensional observed space. However, the algorithm is sensitive to several parameters that should b...
