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Conference Object Recognition of Characters on Vehicle License Plates;(2010) Tora,H.; Bora,K.In this study, a simple and effective method is proposed for segmenting alphanumeric and numeric characters on vehicle license plates and recognizing the segmented characters.The proposed approach is basically based on template matching technique. Features used for matching are obtained by scanning the segmented characters from left-to-right, right-to-left, top-to-bottom, and bottom-to-top. The features extracted in this way reveals the fact that how a character is moving and changing along its four-side.The character recognition is accomplished by using this information of the character.Experiments done show that successful results are obtained. ©2010 IEEE.Conference Object Citation - Scopus: 1Performance Evaluation of Self Organizing Neural Networks for Clustering in Esm Systems;(IEEE Computer Society, 2014) Gencol,K.; Tora,H.Electronic Support Measures (ESM) system is an important function of electronic warfare which provides the real time projection of radar activities. Such systems may encounter with very high density pulse sequences and it is the main task of an ESM system to deinterleave these mixed pulse trains with high accuracy and minimum computation time. These systems heavily depend on time of arrival analysis and need efficient clustering algorithms to assist deinterleaving process in modern evolving environments. On the other hand, self organizing neural networks stand very promising for this type of radar pulse clustering. In this study, performances of self organizing neural networks that meet such clustering criteria are evaluated in detail and the results are presented. © 2014 IEEE.Conference Object Citation - Scopus: 1Higher Order Statistical Analysis of Turkish Phones;(IEEE Computer Society, 2014) Tora,H.; Uslu,B.In this study, histograms of Turkish phones were examined using higher order cumulants. As is known, phones constituting a language, are composed of letters as vowels and consonants. These letters can also be grouped as voiced and unvoiced phones. It is observed that unvoiced letters show a Gaussian-like distribution and result in small values of skewness and kurtosis. On the other hand, vowels and voiced consonants lead to a non-Gaussian distribution. Voiced and unvoiced phones are related with their skewness and kurtosis values. It is empirically shown that higher order cumulants are likely to be a feature in describing Turkish phones. © 2014 IEEE.Article Citation - Scopus: 1Vowel Classification Based on Waveform Shapes(ASTES Publishers, 2019) Tora,H.; Karacor,G.; Uslu,B.Vowel classification is an essential part of speech recognition. In classical studies, this problem is mostly handled by using spectral domain features. In this study, a novel approach is proposed for vowel classification based on the visual features of speech waveforms. In sound vocalizing, the position of certain organs of the human vocal system such as tongue, lips and jaw is very effective on the waveform shapes of the produced sound. The motivation to employ visual features instead of classical frequency domain features is its potential usage in specific applications like language education. Even though this study is confined to Turkish vowels, the developed method can be applied to other languages as well since the shapes of the vowels show similar patterns. Turkish vowels are grouped into five categories. For each vowel group, a time domain speech waveform with an interval of two pitch periods is handled as an image. A series of morphological operations is performed on this speech waveform image to obtain the geometric characteristics representing the shape of each class. The extracted visual features are then fed into three different classifiers. The classification performances of these features are compared with classical methods. It is observed that the proposed visual features achieve promising classification rates. © 2019 Advances in Science, Technology and Engineering Systems.All rights reserved.Conference Object Producing Synthetic Speech From Turkish Text Via a Single Sound Synthesizer Ic;(2010) Tora,H.; Cengizler,Ç.In this study, new speech sounds were created for Turkish letters from the allophones listed in SpeakJet Magnevation complex sound synthesizer IC, which is intended for English, by selecting and paring the most similiar phonems. Consequently, Turkish Text to Speech synthesizer was implemented with minimum enviroment elements and no physical modification on IC. Paring based on SAMPA showed that all Turkish phonems can be obtained from English allophones with high compatibility. The text to speech and paring algorithm presented herein is developed to be embedded in a microcontroller and capable to vocalize a random Turkish text with SpeakJet IC.Conference Object An Approach for Perceptual Similarity Detection Between Audios Independent of Genre Via Metadata Extraction and Correlation;(2007) Komsu,F.; Öztoprak,K.; Tora,H.This study presents an approach for perceptual similarity detection between audios independent of genre. The study is formed of three phases; signal pre-processing as the first phase, metadata extraction via various perceptually compatible features as the second phase, and correlation methodology for similarity identification as the third phase. The performance and relative importance of the selected features for perceptual similarity analysis are presented as testing results. Moreover, relative importance of preprocessing is introduced. Using the proposed methodology, perceptual similarity detection between genre independent audios is achieved with a 96.85% performance. Contribution highly lies on the independency of genre.Conference Object Citation - Scopus: 2The Use of Cumulants for Voiced-Unvoiced Segments Identification in Speech Signals;(IEEE Computer Society, 2014) Uslu,B.; Tora,H.In this study, voiced-unvoiced classification performance of Turkish sounds using skewness and kurtosis is examined. The analyses show that higher order cumulants can be employed as a feature in voiced-unvoiced classification that is vital in speech processing applications. Furthermore, it has been shown that cumulants are also useful for identifying voiced and unvoiced segments in noisy speech signals. © 2014 IEEE.Conference Object Citation - Scopus: 2Real Time Infrared Image Enhancement;(2012) Akdeniz,N.; Tora,H.This study evaluates the implementation of Balanced Contrast Limited Adaptive Histogram Equalization (BCLAHE) for infrared images (IR) on an embedded platform. The aim was to achieve real time performance for the operator display target application. The system configured for this aim is a dual processor media application device OMAP3530, which consists of an ARM and a DSP processor. System is configured so that hardware sources are used efficiently and various performance improvement techniques are investigated. Performance analysis is done over IR images with different dynamic range. © 2012 IEEE.Conference Object Citation - Scopus: 3An Alternative Method for Cell Counting;(2011) Özkan,A.; Belgin Işgör,S.; Tora,H.; Uyar,P.; Işcan,M.Cell counts and classification of the cells play an important role in the field of microbiology and cell biology. Although there exists many counting processes for cells of interest in suspension, the most basic cell counting process is performed by a person via the microscope. For counting cells the simplest, widely used and the most economic method is the use of hemocytometer counting. In this study, the hemocytometer counting was used but the the cells were counted by a proposed image based approach. The developed technique herein uses neural network along with the Hough transform. © 2011 IEEE.Conference Object Tree Based Neural Network Design for Emotion Identification Analysis;(2011) Tora,H.; Altinay Günler,M.Emotion identification analysis became popular research area nowadays. It can be used in many areas such as physiology, education, murder squad, tendency to crime to get a clue about mental signals of a person. Facial expressions are kind of communication channels that carry sense signals. Therefore, they are as important as speech and body movement. Sometimes they are much more meaningful because of their naturalness. That is why it is appreciated to work on automatically recognition of facial expressions. This paper proposes an approach to recognize facial expressions by using neural network. Using one unit neural network is enough to recognize the facial expressions but using a tree structure neural network increases the accuracy of the results and the performance of the testing set. In this study, it is proposed a tree network architecture which yields better recognition performance. © 2011 IEEE.
