Radovan Stojanovic

Real-Time Vision-Based System for Textile Fabric Inspection

This paper presents an automatic vision-based system for quality control of web textile fabrics. The general hardware and software platform developed to solve this problem is presented and a powerful algorithm for defect inspection is proposed. Based on the improved binary, textural and neural network algorithms the proposed method gives good results in the detection of many types of fabric defects under real industrial conditions, where the presence of many types of noise is an inevitable phenomenon. A high detection rate with good localization accuracy, low rate of false alarms, compatibility with standard inspection tools and low price are the main advantages of the proposed system as well as the overall inspection approach.

Defect detection and classification on web textile fabric using multiresolution decomposition and neural networks

In this paper a pilot system for defect detection and classification of web textile fabric in real-time is presented. The general hardware and software platform, developed for solving this problem, is presented while a powerful novel method for defect detection after multiresolution decomposition of the fabric images is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where many types of noise are present. An artificial neural network, trained by a back-propagation algorithm, performs the defect classification in categories.

An architecture for the VLSI design of systems for time-frequency analysis and time-varying filtering

A flexible system for time-frequency signal analysis is presented. It is based on the S-method, which has a significant advantage in implementation since it can involve, as a key intermediate step, the Short-time Fourier transform or the Hartley transform, each widely studied and commonly used in practice. Signal invariant and signal dependent system forms are presented. Hardware design, for a fixed-point arithmetic, is well-structured and suitable for vlsi implementation. The same hardware, without additional time requirements, may be shared for the simultaneous realization of the fourth order L-Wigner distribution, as well as for the realization of the cross-terms free fourth order polynomial Wigner-Ville distribution. This possibility makes the designed hardware suitable for wide range of the applications. The proposed hardware is applied to the realization of time-varying filtering, as well. Finally, it has been implemented with fpga chips (Field Programmable Gate Array) in order to verify the results on real devices.RésuméCet article présente un système souple pour l’analyse d’un signal en temps et en fréquence. Ce système est fondé sur la méthode S, ce qui facilite la réalisation grâce àl’emploi de la transformation de Fourier àcourt terme et de la transformation de Hartley, bien connues et largement en usage. L’article considère deux variantes suivant que la fenêtre dépend ou non du signal. La conception du matériel, en arithmétique àvirgule fixe, convient bien àune réalisation par vlsi. Le même matériel peut être utilisé simultanément et sans délai supplémentaire pour la réalisation d’une distribution L-Wigner du quatrième ordre et celle d’une distribution Wigner-Ville polynomiale d’ordre quatre. Le matériel proposé est appliqué àla réalisation de filtrages variables dans le temps. Les résultats ont pu être vérifiés grâce àune réalisation àbase de puces fpga.

Multiple-clock-cycle architecture for the VLSI design of a system for time-frequency analysis

Multiple-clock-cycle implementation (MCI) of a flexible system for time-frequency (TF) signal analysis is presented. Some very important and frequently used time-frequency distributions (TFDs) can be realized by using the proposed architecture: (i) the spectrogram (SPEC) and the pseudo-Wigner distribution (WD), as the oldest and the most important tools used in TF signal analysis; (ii) the S-method (SM) with various convolution window widths, as intensively used reduced interference TFD. This architecture is based on the short-time Fourier transformation (STFT) realization in the first clock cycle. It allows the mentioned TFDs to take different numbers of clock cycles and to share functional units within their execution. These abilities represent the major advantages of multicycle design and they help reduce both hardware complexity and cost. The designed hardware is suitable for a wide range of applications, because it allows sharing in simultaneous realizations of the higher-order TFDs. Also, it can be accommodated for the implementation of the SM with signal-dependent convolution window width. In order to verify the results on real devices, proposed architecture has been implemented with a field programmable gate array (FPGA) chips. Also, at the implementation (silicon) level, it has been compared with the single-cycle implementation (SCI) architecture.

A FPGA system for QRS complex detection based on Integer Wavelet Transform

A FPGA system for QRS complex detection based on Integer Wavelet Transform Due to complexity of their mathematical computation, many QRS detectors are implemented in software and cannot operate in real time. The paper presents a real-time hardware based solution for this task. To filter ECG signal and to extract QRS complex it employs the Integer Wavelet Transform. The system includes several components and is incorporated in a single FPGA chip what makes it suitable for direct embedding in medical instruments or wearable health care devices. It has sufficient accuracy (about 95%), showing remarkable noise immunity and low cost. Additionally, each system component is composed of several identical blocks/cells what makes the design highly generic. The capacity of today existing FPGAs allows even dozens of detectors to be placed in a single chip. After the theoretical introduction of wavelets and the review of their application in QRS detection, it will be shown how some basic wavelets can be optimized for easy hardware implementation. For this purpose the migration to the integer arithmetic and additional simplifications in calculations has to be done. Further, the system architecture will be presented with the demonstrations in both, software simulation and real testing. At the end, the working performances and preliminary results will be outlined and discussed. The same principle can be applied with other signals where the hardware implementation of wavelet transform can be of benefit.

Real-time vision system for defect detection and neural classification of Web textile fabric

A real-time pilot system for defect detection and classification of web textile fabric is presented in this paper. The general hardware and software platform, developed for solving this problem, is presented and a powerful novel method for defect detection is proposed. This method gives good results in the detection of low contrast defects under real industrial conditions, where the presence of many types of noise is an inevitable phenomenon. For the defect classification an artificial neural network, trained by using a back-propagation algorithm, is implemented. Using a reduced number of possible defect classes, the system gives consistent and repeatable results with sufficient speed.

A LED–LED-based photoplethysmography sensor

A high sensitivity, low power and low cost sensor has been developed for photoplethysmography (PPG) measurement. It uses standard light emitting diodes (LEDs) as both light emitter and detector, pulse-based signal conversion techniques instead of the classical analogue-to-digital convertors (ADCs) and a general purpose microcontroller for the implementation of measurement protocol. The main advantages of the proposed approach are that it leads to better spectral sensitivity, increased and adjustable resolution, reduction in cost, dimensions and power consumption, and it avoids the need for expensive and precise operation amplifiers, ADCs and other external components. The basic sensing configuration presented uses only two I/O pins and two LEDs and is capable of detecting the PPG signal from a finger or toe. It is then very simple to extract the vital signs such as heart rate and heart rate variability from such a signal. The basic configuration can easily be expanded to include a pulse oximeter for the determination of oxygen saturation (SpO(2)) by the addition of only two more LEDs. The proposed technique is also suitable for a wide range of other photometric applications.

An Efficient Hardware Design of the Flexible 2-D System for Space/Spatial-Frequency Signal Analysis

An efficient multiple clock cycle implementation (MCI) of a flexible system for space/spatial-frequency signal analysis is proposed. It is designed by extending the 1-D MCI architecture to the 2-D case. The proposed system can implement various (almost all commonly used) 2-D space/spatial-frequency distributions (S/SFDs) based on the 2-D short-time Fourier transform (STFT) elements. The designed system is very flexible, since it allows the implemented S/SFDs to take different numbers of clock cycles and to share functional kernel, known as the STFT-to-SM gateway, , within their execution. These are major advantages of the MCI approach, that enable one to optimize critical design performances such as hardware complexity, energy consumption, and cost. The proposed approach is verified by a real-time design of the field-programmable gate array chip that is capable of performing 2-D S/SFDs in real time

Design of an Oximeter Based on LED-LED Configuration and FPGA Technology

A fully digital photoplethysmographic (PPG) sensor and actuator has been developed. The sensing circuit uses one Light Emitting Diode (LED) for emitting light into human tissue and one LED for detecting the reflectance light from human tissue. A Field Programmable Gate Array (FPGA) is used to control the LEDs and determine the PPG and Blood Oxygen Saturation (SpO2). The configurations with two LEDs and four LEDs are developed for measuring PPG signal and Blood Oxygen Saturation (SpO2). N-LEDs configuration is proposed for multichannel SpO2 measurements. The approach resulted in better spectral sensitivity, increased and adjustable resolution, reduced noise, small size, low cost and low power consumption.

Speech-controlled cloud-based wheelchair platform for disabled persons

This paper describes the development of the prototype speech controlled cloud based wheelchair platform. The control of the platform is implemented using low-cost available speech WebKit in the cloud. Besides the voice control, the GUI is implemented which works in the web browser as well as on the mobile devices providing live video stream. The platform is based on Mini PC running Ubuntu Linux and Arduino UNO Microcontroller. Software development was done in JavaScript / ECMA Script.