Accepted Papers

  • REAL-TIME MOUTH DEFECTS DETECTION ON MILITARY CARTRIDGE CASES
    Semra Aydin1, Refik Samet2 and Omer Faruk Bay3,1,3Gazi University,2Ankara University,Turkey
    ABSTRACT

    A military cartridge includes four elements; case, capsule, ammunition and powder. While manufacturing, defects may occur in the case. These defects should be detected and the defected cases should be separated. Defects could occur in the mouth, surface and primer parts of the case. This paper proposes the methodology that involves the real-time inspection of the defects in the mouth part of the cases using image processing techniques. The algorithms of the proposed methodology were implemented on real images and the obtained results have showed that common defects such as split and dent defects occurring on the mouth part of the case can be detected with high accuracy.

  • PORTABLE ADQUISITION AND GESTURE RECOGNIZING OF HAND GESTURES INTERFACE WITH ELECTROMYOGRAFY
    E. Aguilar,M. Chauca,Electronic engineering School,National University of Callao,Peru
    ABSTRACT

    This paper will talk about the algorithms and methods used for the creation of a hand gesture recognizing interface. This interface will consist of a microcontroller attached to a instrumentation amplifier circuit. The hand gesture recognizing interface will have several applications, like medicine, Virtual Reality and will not be limited to use by disabled people. Thus the results lay in more than 90% of accuracy, while mantaining low power consumption and needed portability for several applications. The interface may be used alone or connected to a computer or smartphone for interaction with programs interfaced through an API designed for the interface.

  • ROBOT-MANIPULATOR TELEPORTATION BASED ON OPTICAL TRACKING’S ACCURACY
    Pooria Ghanooni1 and Saeed Toosizadeh2, Department of Electronic Engineering, Islamic Azad University, Mashhad Branch
    ABSTRACT

    Stereo Vision Tracker Is a New Method for Virtual and Augmented Reality Applications to estimate position and orientation of bodies' parameters in an operation area that is mentioned in this article. Tracking is based on positioning and indexing of colored markers in two cameras. Accuracy is guaranteed By Comparison of Cube Interpolation and Center Of Gravity methods to obtain center of each marker. We used 5 active markers with special layout on the human’s hand to get head of hand’s coordinate to move gripper of robot’s arm in same position using D-H inverse kinematic. For experimental results, an application is written in C++ language by C++builder XE2 environment.

  • PAROXYSMAL ATRIAL FIBRILLATION (PAF) SCREENING BY ENSEMBLE LEARNING
    Firat Bilgin,1Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey
    ABSTRACT

    Ensemble learning is a combining method of using a combination of different experts to get better results in pattern classification. In this study, ensemble learning was used for the aim of PAF screening, i.e. finding whether a person is PAF patient or not from his/her ectopic-free ECG records. Both hierarchical and parallel structures of ensemble learning were tried To train experts, k–fold cross validation and bootstrap sampling methods were used and their performances were compared. Four different types of classifiers were used as experts. Dataset used consists of electrocardiogram (ECG) records from both PAF patients and non-PAF subjects. The results obtained are presented in tables.

  • USING THE MANDELBROT SET TO GENERATE PRIMARY POPULATIONS IN THE GENETIC ALGORITHM AND REVERSE ORDER IN ORDER TO ENCRYPT THE IMAGE
    Elaheh Aghamohammadi 1, Zeinab Amani 1, Maryam Rastgarpour2,1Islamic Azad University,E-Campus, Tehran, Iran ,2 Islamic Azad University, Saveh Branch, Saveh, Iran
    ABSTRACT

    Nowadays, finding a way to secure media is common with the growth of digital media. An effective method for the secure transmission of images can be found in the field of visual cryptography. There is a growing interest in the use of visual cryptography in security application. Since this method is used for secure transmission of images, many of the methods are developed based on the original algorithm proposed by Naor and Shamir in 1994. In this paper, a new hybrid model is used in cryptography of images which is composed of Mandelbrot algorithm and genetic algorithm. In the early stages of proposal, a number of encrypted images are made by using the Mandelbrot algorithm and the original picture and in the next stage, these encrypted images are used as the initial population for the genetic algorithm. At each stage of the genetic algorithm, the answer of previous iterations is optimized to get the best encoding image. Also, in the proposed method, we can achieve the decoded image by a reverse operation from the genetic algorithm. The best encrypted image is an image with high entropy and low correlation coefficient. According to the entropy and correlation coefficient of the proposed method compared with existing methods, it is observed that our method gets better results in both of them.

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