Advances in Pattern Recognition - ICAPR 2001 : Second International Conference Rio de Janeiro, Brazil, March 11-14, 2001 Proceedings / edited by Sameer Singh, Nabeel Murshed, Walter Kropatsch.

Format:

Book

Contributor:

Singh, Sameer, 1970- editor.

Murshed, Nabeel, editor.

Kropatsch, W. (Walter), editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science 0302-9743 ; 2013.

Lecture Notes in Computer Science, 0302-9743 ; 2013

Language:

English

Subjects (All):

Pattern perception.

Optical data processing.

Computer graphics.

Natural language processing (Computer science).

Pattern Recognition.

Image Processing and Computer Vision.

Computer Graphics.

Natural Language Processing (NLP).

Local Subjects:

Pattern Recognition.

Image Processing and Computer Vision.

Computer Graphics.

Natural Language Processing (NLP).

Physical Description:

1 online resource (XIV, 482 pages).

Edition:

First edition 2001.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2001.

System Details:

text file PDF

Summary:

The paper is organized as follows: In section 2, we describe the no- orientation-discontinuity interfering model based on a Gaussian stochastic model in analyzing the properties of the interfering strokes. In section 3, we describe the improved canny edge detector with an ed- orientation constraint to detect the edges and recover the weak ones of the foreground words and characters; In section 4, we illustrate, discuss and evaluate the experimental results of the proposed method, demonstrating that our algorithm significantly improves the segmentation quality; Section 5 concludes this paper. 2. The norm-orientation-discontinuity interfering stroke model Figure 2 shows three typical samples of original image segments from the original documents and their magnitude of the detected edges respectively. The magnitude of the gradient is converted into the gray level value. The darker the edge is, the larger is the gradient magnitude. It is obvious that the topmost strong edges correspond to foreground edges. It should be noted that, while usually, the foreground writing appears darker than the background image, as shown in sample image Figure 2(a), there are cases where the foreground and background have similar intensities as shown in Figure 2(b), or worst still, the background is more prominent than the foreground as in Figure 2(c). So using only the intensity value is not enough to differentiate the foreground from the background. (a) (b) (c) (d) (e) (f).

Contents:

INVITED TALKS

Towards Bridging the Gap between Statistical and Structural Pattern Recognition: Two New Concepts in Graph Matching

Learning and Adaptation in Robotics

Image-based self-localization by means of zero phase representation in panoramic images

NEURAL NETWORKS and COMPUTATIONAL INTELLIGENCE

A Cascaded Genetic Algorithm for efficient optimization and pattern matching

Using Unlabelled Data to Train a Multilayer Perceptron

A Neural Multi -Expert Classification System for MPEG Audio Segmentation

Pattern Recognition with Quantum Neural Networks

Pattern Matching and Neural Networks based Hybrid Forecasting System

Invariant Face Detection in Color Images Using Orthogonal Fourier-Mellin Moments and Support Vector Machines

CHARACTER RECOGNITION and DOCUMENT ANALYSIS

Character Extraction from Interfering Background - Analysis of Double-sided Handwritten Archival Documents

An Enhanced HMM Topology in an LBA Framework for the Recognition of Handwritten Numeral Strings

Segmentation of Printed Arabic Text

A Time-Length Constrained Level Building Algorithm for Large Vocabulary Handwritten Word Recognition

Preventing Overfitting in Learning Text Patterns for Document Categorization

Image Document Categorization using Hidden Tree Markov Models and Structured Representations

Handwriting Quality Evaluation

FEATURE SELECTION and ANALYSIS

Texture Based Look-Ahead for Decision-Tree Induction

Feature Based Decision Fusion

Feature Selection Based on Fuzzy Distances Between Clusters: First Results on Simulated Data

Efficient and Effective Feature Selection in the Presence of Feature Interaction and Noise

Integrating Recognition Paradigms in a Multiple-path Architecture

A New Geometric Tool for Pattern Recognition - An Algorithm for Real Time Insertion of Layered Segment Trees

PATTERN RECOGNITION and CLASSIFICATION

Improvements in K-Nearest Neighbor Classification

Branch and Bound Algorithm with Partial Prediction for Use with Recursive and Non-Recursive Criterion Forms

Model Validation for Model Selection

Grouping via the Matching of Repeated Patterns

Complex Fittings

Application of adaptive committee classifiers in on-line character recognition

Learning Complex Action Patterns with CRGST

IMAGE and SIGNAL PROCESSING APPLICATIONS

Identification of electrical activity of the brain associated with changes in behavioural performance

Automatic Camera Calibration for Image Sequences of a Football Match

Locating and Tracking Facial Landmarks Using Gabor Wavelet Networks

Complex Images and Complex Filters: A Unified Model for Encoding and Matching Shape and Colour

White Matter/Gray Matter Boundary Segmentation Using Geometric Snakes: A Fuzzy Deformable Model

Multiseeded Fuzzy Segmentation on the Face Centered Cubic Grid

IMAGE FEATURE ANALYSIS and RETRIEVAL

3D Wavelet based Video Retrieval

Combined Invariants to Convolution and Rotation and their Application to Image Registration

Modelling Plastic Distortion in Fingerprint Images

Image Retrieval Using a Hierarchy of Clusters

Texture-adaptive active contour models

A Generalized Local Binary Pattern Operator for Multiresolution Gray Scale and Rotation Invariant Texture Classification

Analysis of Curved Textured Surfaces Using Local Spectral Distortion

Texture Analysis Experiments with Meastex and Vistex Benchmarks

TUTORIALS

Advances in Statistical Feature Selection

Learning-Based Detection, Segmentation and Matching of Objects

Automated Biometrics.

Other Format:

Printed edition:

ISBN:

978-3-540-44732-0

9783540447320

Access Restriction:

Restricted for use by site license.