Adisorn Leelasantitham

A match of X-ray teeth films using image processing based on special features of teeth

This paper presents a match of X-ray teeth films using image processing based on special features of teeth. This method will help the dental doctors to match simply a pair of teeth using the special features of the teeth films. Teethpsilas pictures are scanned and adjusted by a scanner and a computer, respectively, as well as then they are converted into binary code and decoded to the direction code (chain code). The chain code of each picture is compared with the statistical chain code. Therefore, the percentage of the same chain code is approximately 90% (i.e. matching same patterns) for the comparison of one root to one root (7 times) and two roots to two roots (7 times) while the percentage of the same chain code is reduced at relatively below 50% (i.e. matching different patterns) for comparison of one root to two roots (2 times).

Digital biometric facial image encryption using chaotic cellular automata for secure image storages

This paper presents the digital image encryption scheme for biometric facial image using Cellular Automata (CA) for secure image storage. The proposed scheme is relatively simple using a segmentation of CA binary image with embedded secret keys generated by the third class of well-known Wolfram Cellular Automata that exhibits chaotic patterns. Such segmented CA binary image is diffused to the shuffled and bit-plane separated of the original biometric facial image through to XOR operations. Experiments have been performed in MATLAB using a standard digital biometric facial image with the size of 160×160 pixels. Encryption qualitative performances are evaluated through pixel density histograms, 2-dimensional power spectral density, and vertical, horizontal, and diagonal correlation plots. For the encryption quantitative measures, correlation coefficients, entropy, NPCR and UACI are realized. Demonstrations of wrong-key decrypted image are also included. The proposed encryption scheme offers a potential alternative to digital biometric facial image storage in a various applications such as in border security control, payment system, or in crime prevention, detection, and forensics.

A study of performances on an automatic IEEE 802.11g wireless-standard robot using infrared sensors

This paper presents a study of performances on an automatic wireless robot using IEEE 802.11g standard and infrared sensors. The robot acts a personal computer (PC) controlling equipments (e.g. motors) through a printer port. Window XP is setup on the PC robot which is received a command from notebook (only Start / Stop commands) linked through the use of a wireless router and a real-time streaming protocol (RTSP) program. The study of performances on the automatic wireless robot is tested in three patterns of obstacles i.e. ┐,┌ and Π. In the results, the robot can avoid a hindrance when infrared sensors detect the obstacles, then it will move backward direction in the length of 60 cm and move forward direction in the angle of 45°. The sensors can detect colors (except black color) and opaque but they cannot detect clear glass. In addition, the delay time and the maximum distance of transmitting and receiving images are approximately at 0.1s and 40m, respectively.

Detection and classification of moving Thai vehicles based on traffic engineering knowledge

This paper presents detection and classification of moving Thai vehicles based on traffic engineering knowledge. The proposed technique consists of two main parts as follows. The first part is the detection of moving vehicles using image tracking methods e.g. background and foreground (BG/FG) detection and blob tracking. Such methods can provide the values of vehicle features such as position, length (L) and width (W). The second part is the classification of Thai vehicles based on traffic engineering knowledge which is traffic management for not only controlling traffic lights on a crossroad but also calculating volume/capacity ratio and queue length. Therefore Thai vehicles normally can be separated into five groups i.e. first: bicycle, motorcycle and motor tricycle (Tuk-Tuk); second: passenger car, pickup, van and passenger pickup; third: six-wheel truck and mini bus; fourth: ten-wheel truck and big bus; fifth: eighteen-wheel truck and trailer. From above reasons, the second part uses the key features of size (W, L and W/L ratio) from each group which are applied to a decision-tree method for classifying Thai-vehicle groups. The result shows that the use of one input feature is sufficient for the differentiation between 4-group with an overall classification accuracy of 97.37%.

A simulation of 6R industrial articulated robot arm using backpropagation neural network

This paper presents a simulation of a 6 degrees-of-freedom (6R) articulated robot arm using backpropagation neural network to solve the problem regarding inverse kinematics for the industrial articulated robot. The Denavit - Hartenberg model is used to analyze the robot arm movement. Next, the forward kinematics is used to identify the relationships for each joint of the robot arm and to determine various parameters for learning system of random neural network for 5,000 data points. The simulation results show that the robot arm can move to target positions with precision, and the average error for the entire 6 joints is at approximately 4.03 degrees.

A high-frequency low-power all-NMOS all-current-mirror sinusoidal quadrature oscillator

A high-frequency low-power sinusoidal quadrature oscillator is presented through the use of only current mirrors where the small-signal paths are realized through all NMOS transistors. The technique is relatively simple based on (i) inherent time constants of current mirrors, i.e. the internal capacitances and the transconductance of a diode-connected NMOS, (ii) a negative resistance formed by a transconductance of a diode-connected NMOS load of a current mirror. No external passive components are required. As a particular example, a 2.83-GHz, 0.374-f/sub T/, 0.38-mW sinusoidal quadrature oscillator is demonstrated. Total harmonic distortions (THD) are less than 0.8 %. The oscillation frequency is current-tunable over a range of 640 MHz or 22.62 %. The amplitude matching and the quadrature phase matching are better than 0.04 dB and 0.17/spl deg/, respectively. A figure of merit called CNR/sub norm/ is 158.23 dBc/Hz at the 2 MHz offset from 2.83 GHz.

Investigation of chest x-ray images based on medical knowledge and balanced histograms

The primary checking for our health at hospital needs to include a chest x-ray as routine diagnosis because it effectively illustrates the lung diseases especially tuberculosis or lung cancer which are asymptomatic earlier. It is a convenient and quick process with a low cost in comparison with other studies. This paper presents an investigation of the radiographs of lung from the chest x-ray using on medical knowledge and balanced histogram. Selected images of lungs are depicted by the use of an active contour (e.g. snake algorithm) to find two regions of lungs (left and right). Then, such two regions of lungs are represented for two histograms which are profiles of two lung patterns. Such two histograms are compared for normal and abnormal lungs using a method of center of gravity (COG) to demonstrate the difference of both lung radiographs. If two histograms are balance, then the result is a normal case. However, if they are not balance, then it is an abnormal case. For the experimental results, the overall accuracy is at approximately 95% which there are 100 samples of patients for testing their lung images. All samples are previously checked from the medical doctors.

A method of detecting tonsillitis images based on medical knowledge and neural network

Tonsillitis is a disease occurring mostly in child and adults as this disease may take to the other effects. Nowadays, a detection of tonsil grand exploits medical doctors diagnosis to check on oral cavity. Therefore, this paper presents a method of detecting tonsillitis images based on medical knowledge and neural network (NN); as well as, the paper considers three important factors which can be indicated in swelling by the pictures in terms of a) the ratio of tonsil grand dimension, b) average of tonsil grand color and c) surface of tonsil grand as it is purulent (yes/no) using two dimensional Fast Fourier Transform (2D FFT). Finally, the three factors are inputted into NN, and samples of 30 pictures are used for training into the NN which is divided by tonsillitis patience 15 pictures and usual tonsil grand 15 pictures. In the experimental results, 20 pictures are tested to compare with the result of the medical doctors demonstration as the result of correction approximately at 90%.

A high-frequency low-power sinusoidal quadrature oscillator using only CMOS current mirrors

A high-frequency low-power sinusoidal quadrature oscillator is presented through a new technique using only CMOS current mirrors. The technique is relatively simple based on (1) internal capacitances of CMOS current mirrors and (2) a resistor of a CMOS current mirror for a negative resistance. No external capacitances or inductances are required. As a particular example, a 3.02-GHz, 0.4-f/sub T/, 0.31-mW, CMOS sinusoidal quadrature oscillator has been demonstrated. The oscillation frequency (f/sub 0/) is 3.02 GHz. The ratio of (f/sub 0//f/sub T/) is 0.4. The power consumption is low at approximately 0.31 mW. Total harmonic distortions (THD) are less than 0.3%. The oscillation frequency is current-tunable over a range of 660 MHz or 21.85%. The amplitude matching and the quadrature phase matching are better than 0.029 dB and 0.15/spl deg/, respectively. A figure of merit called CNR/sub norm/ is 161.68 dBc/Hz at the 2 MHz offset from 3.02 GHz. Comparisons to other approaches are also presented.

A partial encryption scheme using absolute-value chaotic map for secure electronic health records

This paper presents a partial encryption scheme using absolute-value chaotic map for secure electronic health records (EHR). The HER system has been an emerging technology that allows medical personals to create, manage, and control medical data electronically through specific database or even web browsers. The proposed encryption scheme realizes XOR operations between separated planes of binary gray-scale image and a binaty imgae generated by an absolute-value chaotic map. The proposed is relatively simple containning a single absolute-value function with two constants and offers complex and robust dynamical behaviors in terms of random output values. Experiments have been performed in MATLAB using a magnetic resosnace image which is divided into 64 sub-blocks and 13th itterations were proceeded for encryption. Encryption qualitative performances are evaluated through pixel density histograms, 2-dimensional power spectral density, and vertical, horizontal, and diagonal correlation plots. For the encryption quantitative measures, correlation coefficients, entropy, NPCR and UACI are realized. Demonstrations of wrong-key decrypted image are also included. The proposed encryption scheme offers a potential alternative to a secure medical data records and web browsing through clound computing systems.