Cengiz Gungor

Technical Section: Linear approximation of Bidirectional Reflectance Distribution Functions

Various empirical and theoretical models of the surface reflectance have been introduced so far. Most of these models are based on functions with non-linear parameters and therefore faces some computational difficulties involved in non-linear optimization processes. In this paper, we introduce a new approach for approximating Bidirectional Reflectance Distribution Functions (BRDF) by employing response surface methodology. The proposed model employs principal component transformations of the explanatory variables which are essentially functions of incoming and outgoing light directions. The resulting model is linear and can be used to represent both isotropic and anisotropic reflectance for diffuse and glossy materials. Considering some widely used reflection models including the Ward model, the Ashikhmin-Shirley model and the Lafortune model, we demonstrate empirically that satisfactory approximations can be made by means of the proposed general, simple and computationally efficient linear model.

A histogram smoothing method for digital subtraction radiography

Digital subtraction radiography is a powerful technique for the detection of changes in serial radiographs. Among the others, contrast correction is a basic step for comparing the radiographs. Ruttimanns algorithm is widely used for contrast correction. In this study we propose a technique which is based on smoothing the empirical distribution of the reference image to improve Ruttimanns algorithm. Cardinal splines were used for smoothing the empirical distribution. Results based on clinical and simulated data showed that the proposed technique has outperformed the Ruttimanns algorithm. Relationship between the color depth and contrast differences was also investigated in terms of peak to signal ratio metric.

An Interactive Cryptanalysis Algorithm for the Vigenere Cipher

Though it dates back centuries, Vigenere Cipher is still a practical encryption method that can be edffciently used for many applications. We have designed and implemented an interactive cryptanalysis software based on the Kasiski test, and a novel use of the Index of Coincidence (IC) concept. Our results show that cryptanalysis is possible for very short text lengths where classical cryptanalysis methods fail. Furthermore, we have observed that our software which is designed to work on English based ciphertexts, can be successfully executed on ciphertexts based on other languages. Along the way, we also compute and report the IC values for Turkish and some other languages under a diffierent number of enciphering alphabets.

Improving visual perception of augmented reality on mobile devices with 3D red-cyan glasses

In this work, we study the understanding of 3D visual objects which are generated by augmented reality techniques. 3D glasses are typically highly priced, and so they are not purchasable for most consumers. Instead, we consider low-priced red-cyan (anaglyph) glasses. We generate the left and right views so that they are comfortable for human eyes.

Registration and optimization in entropic graphs using branch skeleton features

25th Signal Processing and Communications Applications Conference, SIU 2017; Antalya; Turkey; 15 May 2017 through 18 May 2017In image registration process, it is necessary to find the similarity of the images and the translation, rotation and scaling transformation parameter values that maximize the similarity between the two images. When the similarity measure and related parameters are calculated, information theory based entropic graphs can be used. In this study, similarity and optimization measures are compared on different entropic graphs. It has been seen that skeleton branch feature points to build entropic graphs give successful results.

A new subtraction radiography approach for dental applications

In this project we present a novel approach for identifying the landmarks on dental images. The proposed method is based on exploiting some well known characteristics of hard tissue including bone structures. Images are defined in terms of univariate and bivariate probability distributions and certain characterizations of these distributions are used to identify the underlying landmarks. Based on the proposed algorithm, a software package which can be used to identify the landmarks manually and automatically has been developed.