discrimination of different serbian pronunciations from shtokavian dialect

Abstract This paper proposes a new methodology for discrimination of different pronunciations in the Shtokavian dialect of the Serbian language. At the first, the written language (Unicode text) is converted into codes according to the energy status of each character in the text-line. Such a set of codes is seen as a grayscale image. Then, the local structures of the image are explored by local binary operators. It creates a vector set which differentiates various pronunciations of the Serbian language. The experiment is performed on fifty documents given in Serbian language. A comparison performed between the proposed method and the n -gram method shows its clear advantage

Statistics Oriented Preprocessing of Document Image

Old printed documents represent an important part of our cultural heritage. Their digitalization plays an important role in creating data and metadata. The paper proposed an algorithm for estimation of the global text skew. First, document image is binarized reducing the impact of noise and uneven illumination. The binary image is statistically analyzed and processed. Accordingly, redundant data have been excluded. Furthermore, the convex hulls are established encircling each text object. They are joined establishing connected components. Then, the connected components in complementary image are enlarged with morphological dilation. At the end, the biggest connected component is extracted. Its orientation is similar to the global orientation of text document which is calculated by the moments. Efficiency and correctness of the algorithm are verified by testing on a custom dataset

Three-Parametric Cubic Interpolation for Estimating the Fundamental Frequency of the Speech Signal

In this paper, we propose a three-parametric convolution kernel which is based on the one-parameter Keys kernel. The first part of the paper describes the structure of the three-parameter convolution kernel. Then, a certain analytical expression for finding the position of the maximum of the reconstructed function is given. The second part presents an algorithm for estimating the fundamental frequency of the speech signal processing in the frequency domain using Picking Picks methods and parametric cubic convolution. Furthermore, the results of experiments give the estimated fundamental frequency of speech and sinusoidal signals in order to select the optimal values of the parameters of the proposed convolution kernel. The results of the fundamental frequency estimation according to the mean square error are given by tables and graphics. Consequently, it is used as a basis for a comparative analysis. The analysis derived the optimal parameters of the kernel and the window function that generates the least MSE. Results showed a higher efficiency in comparison to two or three-parameter convolution kernel

Self-Organizing Map Classification of the Extremely Low-Frequency Magnetic Field Produced by Typical Tablet Computers

Abstract In this paper, the extremely low frequency magnetic field produced by the tablet computers is explored. The measurement of the tablet computers' magnetic field is performed by using a measuring geometry previously proposed for the laptop computers. The experiment is conducted on five Android tablet computers. The measured values of the magnetic field are compared to the widely accepted TCO safety standard. Then, the results are classified by the Self-Organizing Map method in order to create different levels of safety or danger concerning the magnetic field to which tablet computer users are exposed. Furthermore, a brief comparison of the obtained magnetic field levels with the ones from typical laptops is performed. At the end, a practical suggestion on how to avoid the high exposure to the low frequency magnetic field emitted by the tablet computers is given

Basic Test Framework for the Evaluation of Text Line Segmentation and Text Parameter Extraction

Text line segmentation is an essential stage in off-line optical character recognition (OCR) systems. It is a key because inaccurately segmented text lines will lead to OCR failure. Text line segmentation of handwritten documents is a complex and diverse problem, complicated by the nature of handwriting. Hence, text line segmentation is a leading challenge in handwritten document image processing. Due to inconsistencies in measurement and evaluation of text segmentation algorithm quality, some basic set of measurement methods is required. Currently, there is no commonly accepted one and all algorithm evaluation is custom oriented. In this paper, a basic test framework for the evaluation of text feature extraction algorithms is proposed. This test framework consists of a few experiments primarily linked to text line segmentation, skew rate and reference text line evaluation. Although they are mutually independent, the results obtained are strongly cross linked. In the end, its suitability for different types of letters and languages as well as its adaptability are its main advantages. Thus, the paper presents an efficient evaluation method for text analysis algorithms

An approach to the low-resistance measurement

The paper presents the real instrument functional characteristics and describes the way of practical solutions of its performance improvement. It presents the design process of the instrument made for resistance measuring. In order to achieve desired objectives, a great number of experiments have been carried out during the development. Basically, the comparison method has been applied. At first, it was intended for the small resistor measuring as a single range unit. Later, the device has been improved and upgraded for a wide range resistance measuring. Finally, some of the difficulties have been detected and explained as well. The paper contains solutions developed and applied for their overcoming. [Projekat Ministarstva nauke Republike Srbije, br. TR 33037 i br. TR 34005

Analysis of the Extremely Low Frequency Magnetic Field Emission from Laptop Computers

This study addresses the problem of magnetic field emission produced by the laptop computers. Although, the magnetic field is spread over the entire frequency spectrum, the most dangerous part of it to the laptop users is the frequency range from 50 to 500 Hz, commonly called the extremely low frequency magnetic field. In this frequency region the magnetic field is characterized by high peak values. To examine the influence of laptop’s magnetic field emission in the office, a specific experiment is proposed. It includes the measurement of the magnetic field at six laptop’s positions, which are in close contact to its user. The results obtained from ten different laptop computers show the extremely high emission at some positions, which are dependent on the power dissipation or bad ergonomics. Eventually, the experiment extracts these dangerous positions of magnetic field emission and suggests possible solutions

A New Approach to Water Flow Algorithm for Text Line Segmentation

This paper proposes a new approach to water flow algorithm for the text line segmentation. Original method assumes hypothetical water flows under a few specified angles to the document image frame from left to right and vice versa. As a result, unwetted image frames are extracted. These areas are of major importance for text line segmentation. Method modifications mean extension values of water flow angle and unwetted image frames function enlargement. Results are encouraging due to text line segmentation improvement which is the most challenging process stage in document image processing

Exploring the usability of the text-based CAPTCHA on tablet computers

This paper analyses and discusses the usability aspect of the text-based CAPTCHA in terms of response time and success in solving the CAPTCHA on tablet computers. The response time is the time spent by the user to find a solution to the CAPTCHA. The analysis is separately conducted on text-based CAPTCHA with only text and numbers. Then, the results are compared and the differences in response time and success in solving the two types of CAPTCHA are underlined. This is accomplished by asking 125 Internet users to solve the text-based CAPTCHA on the tablet computer. Their gender, age, education level, Internet experience, response time and success in solving two types of text-based CAPTCHA are collected in a dataset. Then, advanced statistical analysis by association rule mining is performed. It shows the dependence of the response time and success in solving the CAPTCHA on co-occurrence of gender, age, education level and Internet experience and the strength of this dependence by support, confidence and lift measures. This study provides relevant information for designing new CAPTCHAs which may be more accustomed to specific types of Internet users