An adaptive method for video denoising based on the ICI rule

This paper presents an adaptive video denoising technique based on the intersection of confidence intervals (ICI) rule used for adaptive filter support size calculation. The method is applied to three real-life video signals and its denoising performance is compared to a fixed size filter support based method resulting in a significant estimation error reduction in terms of the average frame peak signal-to-noise ratio (PSNR) improvement. The average frame PSNR obtained by using the here presented ICI based video denoising method is increased by up to 14.64 dB and by up to 23.74 dB when compared to the fixed size filter support based method. Furthermore, unlike the fixed size filter support based method, the adaptive ICI based method is shown to be efficient in a moving object edge preserving, while avoiding its blurring. The method performs well for both video signals obtained by recording stationary scenes, and video signals of moving objects, which are far more often encountered in practical applications, whereas the fixed size filter support based method is limited only to video signals of stationary scenes

Remote laboratories in engineering education: automation system design

This paper deals with the usage of a remote laboratory as a platform for integrating learning into engineering education. It also shows a concept and partial implementation results of a remote laboratory for designing automation systems. Advantages and disadvantages of such a system are elaborated from the didactical, technological and economical point of view and accordingly, their results are presented. Also, an overview of simulation and implementation results is included.. Finally, directions for future work and an on-line application have been outline

Detecting the number of components in a non-stationary signal using the Rényi entropy of its time-frequency distributions

A time-frequency distribution provides many advantages in the analysis of multicomponent non-stationary signals. The simultaneous signal representation with respect to the time and frequency axis defines the signal amplitude, frequency, bandwidth, and the number of components at each time moment. The Rényi entropy, applied to a time-frequency distribution, is shown to be a valuable indicator of the signal complexity. The aim of this paper is to determine which of the treated time-frequency distributions (TFDs) (namely, the Wigner-Ville distribution, the Choi-Williams distribution, and the spectrogram) has the best properties for estimation of the number of components when there is no prior knowledge of the signal. The optimal Rényi entropy parameter α is determined for each TFD. Accordingly, the effects of different time durations, bandwidths and amplitudes of the signal components on the Rényi entropy have been analysed. The concept of a class, when the Rényi entropy is applied to TFDs, is also introduced

DIRECTIONALITY ASSESSMENT OF DIGITAL IMAGES CONTENT USING FAN FILTERS

U ovom je radu predložena metoda određivanja usmjerenosti sadržaja digitalnih slika. U tu su svrhu projektirane skupine filtara sa svojstvima različitog propuštanja samo određenih prostornih frekvencija. Područje propuštanja takvih filtara je klinastog oblika s određenim zakretom s obzirom na frekvencijske osi. Rezultati određivanja usmjerenosti sadržaja prikazani su za sintetske slike prostornih valova kao i za neke realne slike.In this paper, we propose a method for assessing the directionality of digital images’ content. For that purpose, special filter groups are designed that allow the passage of only predefined spatial frequency content. The passband of the filters is wedge-shaped with a predetermined rotation with respect to the frequency axes. Directionality assessment results are presented for both synthetic images of spatial waves and some real-world images

DIRECTIONAL DIGITAL FILTERS FOR FINGERPRINT RECOGNITION

U ovome radu, analizirali smo slike otisaka prstiju korištenjem usmjerenih digitalnih filtara. Riječ je o filtrima klinastoga oblika područja propuštanja, tzv. fan filtri. Primjenom takvih filtara razvijena je metoda određivanja usmjerenosti papilarnih linija slike otiska prsta u svrhu određivanja podudarnosti dvaju otisaka. Dobiveni rezultati potvrđuju pozitivna očekivanja o primjeni fan filtara u području biometrije.In this paper we have analyzed fingerprint images using directional digital filters. The filters have a double wedge-shaped pass band, hence the name fan filters. Using these filters, a method is developed for determining the ridge orientation for the purpose of comparing two fingerprints. The obtained results confirm the applicability of fan filters in biometric applications

DIRECTIONALITY ASSESSMENT OF DIGITAL IMAGES CONTENT USING FAN FILTERS

U ovom je radu predložena metoda određivanja usmjerenosti sadržaja digitalnih slika. U tu su svrhu projektirane skupine filtara sa svojstvima različitog propuštanja samo određenih prostornih frekvencija. Područje propuštanja takvih filtara je klinastog oblika s određenim zakretom s obzirom na frekvencijske osi. Rezultati određivanja usmjerenosti sadržaja prikazani su za sintetske slike prostornih valova kao i za neke realne slike.In this paper, we propose a method for assessing the directionality of digital images’ content. For that purpose, special filter groups are designed that allow the passage of only predefined spatial frequency content. The passband of the filters is wedge-shaped with a predetermined rotation with respect to the frequency axes. Directionality assessment results are presented for both synthetic images of spatial waves and some real-world images