Marcin Iwanowski

Vision-based vehicle speed measurement method

This paper introduces a novel method for vehicle speed detection based exclusively on visual information. The proposed system consisting only of a digital camera and a computer is able to identify both the speed of the passing vehicle and its licence plate numbers, which makes it an interesting alternative to existing and expensive photoradar systems. The principle of operation is simple: vehicles are identified by their licence plates and their speed is measured based on the vertical difference of their position in consecutive images. An experimental evaluation shows the high accuracy of vehicle speed measurement, comparable to the one provided by comercially available radar-based systems.

Morphological Boundary Pixel Classification

This paper presents the method which allow classifying pixels of the internal boundary of objects on the binary image. The application of morphological tools allows grouping internal boundary pixels into four spatial classes: core boundary, isolated regions, branches and corridors. The classification of boundary pixels provides us with a tool for shape description both locally and globally. This description is used to characterize the pixels themselves as well as to describe the image objects. In the latter case the coefficients based on the quantity of pixels of different classes are calculated. These coefficients may be used as features for pattern recognition.

Pattern recognition using morphological class distribution functions and classification trees

The paper presents an effective and robust method of classifying binary patterns. It starts with classification of foreground pixels of binary image into several spatial classes, which is performed using morphological image processing. By performing this classification with structuring elements of increasing sizes, the spatial class distribution functions are produced. These functions are normalized and sampled in order to obtain feature vectors of constant length that are invariant to pattern translation, rotation and scaling. Such feature vectors are next used to perform tree-based classification.

Detection of the Area Covered by Neural Stem Cells in Cultures Using Textural Segmentation and Morphological Watershed

Monitoring and evaluation of the dynamic of stem cells growth in culture is important in the regenerative medicine as a tool for cells population increasing to the size needed to therapeutic bprocedure. In this paper the automatic segmentation method of cells images from bright field microscope is proposed. It is based on the textural segmentation and morphological watershed. Textural segmentation aims at detecting within the image regions with intensive textural features, which refer to cells. Texture features are detected using local mean absolute deviation measure. Final, precise segmentation is achieved by means of morphological watershed on the gradient image modified by the imposition of minima derived from the result of rough segmentation. The proposed scheme can be applied to segment other images containing object characterized by their texture located on the uniform background.

Binary Shape Characterization Using Morphological Boundary Class Distribution Functions

In the paper a new method for binary shape characterization is proposed. It is based on the analysis of binary image pixels belonging to the internal boundary of an object performed by means of the mathematical morphology. By using morphological operators, internal boundary pixels are classified into three groups. This classification is performed for increasing sizes of structuring elements used. The changes within the class assignments are described by the boundary class distribution functions. These functions may be used as features in the pattern recognition process.

Adaptive and Natural Computing Algorithms

Neural Networks.- Evolution of Multi-class Single Layer Perceptron.- Estimates of Approximation Rates by Gaussian Radial-Basis Functions.- Least Mean Square vs. Outer Bounding Ellipsoid Algorithm in Confidence Estimation of the GMDH Neural Networks.- On Feature Extraction Capabilities of Fast Orthogonal Neural Networks.- Neural Computations by Asymmetric Networks with Nonlinearities.- Properties of the Hermite Activation Functions in a Neural Approximation Scheme.- Study of the Influence of Noise in the Values of a Median Associative Memory.- Impact of Learning on the Structural Properties of Neural Networks.- Learning Using a Self-building Associative Frequent Network.- Proposal of a New Conception of an Elastic Neural Network and Its Application to the Solution of a Two-Dimensional Travelling Salesman Problem.- Robust Stability Analysis for Delayed BAM Neural Networks.- A Study into the Improvement of Binary Hopfield Networks for Map Coloring.- Automatic Diagnosis of the Footprint Pathologies Based on Neural Networks.- Mining Data from a Metallurgical Process by a Novel Neural Network Pruning Method.- Dynamic Ridge Polynomial Neural Networks in Exchange Rates Time Series Forecasting.- Neural Systems for Short-Term Forecasting of Electric Power Load.- Jet Engine Turbine and Compressor Characteristics Approximation by Means of Artificial Neural Networks.- Speech Enhancement System Based on Auditory System and Time-Delay Neural Network.- Recognition of Patterns Without Feature Extraction by GRNN.- Real-Time String Filtering of Large Databases Implemented Via a Combination of Artificial Neural Networks.- Parallel Realizations of the SAMANN Algorithm.- A POD-Based Center Selection for RBF Neural Network in Time Series Prediction Problems.- Support Vector Machines.- Support, Relevance and Spectral Learning for Time Series.- Support Vector Machine Detection of Peer-to-Peer Traffic in High-Performance Routers with Packet Sampling.- Improving SVM Performance Using a Linear Combination of Kernels.- Boosting RVM Classifiers for Large Data Sets.- Multi-class Support Vector Machines Based on Arranged Decision Graphs and Particle Swarm Optimization for Model Selection.- Applying Dynamic Fuzzy Model in Combination with Support Vector Machine to Explore Stock Market Dynamism.- Predicting Mechanical Properties of Rubber Compounds with Neural Networks and Support Vector Machines.- An Evolutionary Programming Based SVM Ensemble Model for Corporate Failure Prediction.- Biomedical Signal and Image Processing.- Novel Multi-layer Non-negative Tensor Factorization with Sparsity Constraints.- A Real-Time Adaptive Wavelet Transform-Based QRS Complex Detector.- Nucleus Classification and Recognition of Uterine Cervical Pap-Smears Using FCM Clustering Algorithm.- Rib Suppression for Enhancing Frontal Chest Radiographs Using Independent Component Analysis.- A Novel Hand-Based Personal Identification Approach.- White Blood Cell Automatic Counting System Based on Support Vector Machine.- Kernels for Chemical Compounds in Biological Screening.- A Hybrid Automated Detection System Based on Least Square Support Vector Machine Classifier and k-NN Based Weighted Pre-processing for Diagnosing of Macular Disease.- Analysis of Microscopic Mast Cell Images Based on Network of Synchronised Oscillators.- Detection of Gene Expressions in Microarrays by Applying Iteratively Elastic Neural Net.- A New Feature Selection Method for Improving the Precision of Diagnosing Abnormal Protein Sequences by Support Vector Machine and Vectorization Method.- Epileptic Seizure Prediction Using Lyapunov Exponents and Support Vector Machine.- Classification of Pathological and Normal Voice Based on Linear Discriminant Analysis.- Efficient 1D and 2D Daubechies Wavelet Transforms with Application to Signal Processing.- A Branch and Bound Algorithm for Matching Protein Structures.- Biometrics.- Multimodal Hand-Palm Biometrics.- A Study on Iris Feature Watermarking on Face Data.- Keystroke Dynamics for Biometrics Identification.- Protecting Secret Keys with Fuzzy Fingerprint Vault Based on a 3D Geometric Hash Table.- Face Recognition Based on Near-Infrared Light Using Mobile Phone.- NEU-FACES: A Neural Network-Based Face Image Analysis System.- GA-Based Iris/Sclera Boundary Detection for Biometric Iris Identification.- Neural Network Based Recognition by Using Genetic Algorithm for Feature Selection of Enhanced Fingerprints.- Computer Vision.- Why Automatic Understanding?.- Automatic Target Recognition in SAR Images Based on a SVM Classification Scheme.- Adaptive Mosaicing: Principle and Application to the Mosaicing of Large Image Data Sets.- Circular Road Signs Recognition with Affine Moment Invariants and the Probabilistic Neural Classifier.- A Context-Driven Bayesian Classification Method for Eye Location.- Computer-Aided Vision System for Surface Blemish Detection of LED Chips.- Detection of Various Defects in TFT-LCD Polarizing Film.- Dimensionality Problem in the Visualization of Correlation-Based Data.- A Segmentation Method for Digital Images Based on Cluster Analysis.- Active Shape Models and Evolution Strategies to Automatic Face Morphing.- Recognition of Shipping Container Identifiers Using ART2-Based Quantization and a Refined RBF Network.- A Local-Information-Based Blind Image Restoration Algorithm Using a MLP.- Reflective Symmetry Detection Based on Parallel Projection.- Detail-Preserving Regularization Based Removal of Impulse Noise from Highly Corrupted Images.- Fast Algorithm for Order Independent Binary Homotopic Thinning.- A Perturbation Suppressing Segmentation Technique Based on Adaptive Diffusion.- Weighted Order Statistic Filters for Pattern Detection.- Real-Time Image Segmentation for Visual Servoing.- Control and Robotics.- A Neural Framework for Robot Motor Learning Based on Memory Consolidation.- Progressive Optimisation of Organised Colonies of Ants for Robot Navigation: An Inspiration from Nature.- An Algorithm for Selecting a Group Leader in Mobile Robots Realized by Mobile Ad Hoc Networks and Object Entropy.- Robot Path Planning in Kernel Space.- A Path Finding Via VRML and VISION Overlay for Autonomous Robot.- Neural Network Control for Visual Guidance System of Mobile Robot.- Cone-Realizations of Discrete-Time Systems with Delays.- Global Stability of Neural Networks with Time-Varying Delays.- A Sensorless Initial Rotor Position Sensing Using Neural Network for Direct Torque Controlled Permanent Magnet Synchronous Motor Drive.- Postural Control of Two-Stage Inverted Pendulum Using Reinforcement Learning and Self-organizing Map.- Neural Network Mapping of Magnet Based Position Sensing System for Autonomous Robotic Vehicle.- Application of Fuzzy Integral Control for Output Regulation of Asymmetric Half-Bridge DC/DC Converter.- Obtaining an Optimum PID Controller Via Adaptive Tabu Search.

Order independence in binary 2d homotopic thinning

This paper investigates binary homotopic 2D thinning in view of its independence of the order of processing image pixels Pixel removal conditions are provided leading to an order independent thinning They are introduced for various types of connectivity Two kinds of pixels to be removed are considered: simple and b-simple Use of each of those pixels yields to different types of order independent thinnings: homotopic marking and local-SKIZ.

Tree-based binary image dissimilarity measure with meta-heuristic optimization

In this paper, we present a method of evaluating binary image dissimilarity based on tree representation and heuristic optimization. Starting from the image, a graph structure of a binary tree is constructed that splits the set of image foreground pixels into consecutive subsets attached to tree nodes. Next, instead of comparing two images themselves, one compares the trees and expresses image dissimilarity as tree dissimilarity, which can be characterized by a nonlinear function. The goal is to find its minimum, as it corresponds with the best match of compared trees. Searching for the minimum would be ineffective with analytical optimization methods. Hence, we have approached the issue with three meta-heuristic algorithms, namely genetic algorithm, particle swarm optimization (PSO) and simulated annealing. The presented results show that PSO achieved the best results. The proposed method is compared with other binary image comparison approaches. The performed tests that are described in the paper show that it outperforms its competitors and can be successfully applied to compare binary images.

Fast Algorithm for Order Independent Binary Homotopic Thinning

In this paper an efficient queue-based algorithm for order independent homotopic thinning is proposed. This generic algorithm can be applied to various thinning versions: homotopic marking, anchored skeletonisation, and the computation of the skeleton of influence zones based on local pixel characterisations. An example application of the proposed method to detect the medial axis of wide river networks from satellite imagery is also presented.

Morphological refinement of an image segmentation

This paper describes a method to improve a given segmentation result in order to produce a new, refined and more accurate segmented image. The method consists of three phases: shrinking of the input partitions, filtering of the input imagery leading to a mask image, and expansion of the shrunk partitions within the filtered image. The concept is illustrated for the enhancement of a land cover data set using multispectral satellite imagery.