Alexander C. Abad

A genetic algorithm and artificial neural network-based approach for the machine vision of plate segmentation and character recognition

This paper proposes a genetic-algorithm and neural network-based approach in the optimization of the process of plate segmentation and character recognition respectively in intelligent transportation systems. Upon the detection of the vehicles plate from a captured image, it is necessary that the individual characters in the detected plate are distinguished. After the process of plate recognition, the recognized plate number can be crossed-referenced against a database to correctly identify the vehicles owner and ultimately penalize him for the traffic rule he violated. The segmentation algorithm captures the region of each character in the detected plate using genetic algorithm. After which, each plate character image is mapped against its corresponding sample character image. This is done by feeding sample character images into an artificial neural network and training the network.

Low cost smart security camera with night vision capability using Raspberry Pi and OpenCV

In order to further maintain peace and provide security to people now a day, Closed-circuit television (CCTV) surveillance system is being utilized. This study focused on the design and implementation of a low cost smart security camera with night vision capability using Raspberry Pi (RPI) and OpenCV. The system was designed to be used inside a warehouse facility. It has human detection and smoke detection capability that can provide precaution to potential crimes and potential fire. The credit card size Raspberry Pi (RPI) with Open Source Computer Vision (OpenCV) software handles the image processing, control algorithms for the alarms and sends captured pictures to users email via Wi-Fi. As part of its alarm system, it will play the recorded sounds: “intruder” or “smoke detected” when there is a detection. The system uses ordinary webcam but its IR filter was removed in order to have night vision capability.

Machine vision of traffic state estimation using fuzzy logic

One of the problems encountered by motorists are congested roads. Current technology cannot easily broadcast the information about which roads are heavily congested and which are not to the motorists. As such, planning of the route to take to their destinations is compromised. This paper proposes a fuzzy logic method approach to the estimation of the traffic state of a road. Images from IP cameras installed in different roads can be used to determine the state of the traffic in an area at any point in time. The vehicles within the image are needed to be detected first via edge detection. As the vehicles are detected within the image, so are their position and size with respect to the whole image are obtained. As such, three different parameters namely vehicle density, distance between neighboring vehicles and vehicle sizes can be computed. Using these three parameters, a fuzzy logic system can be created. Three degrees of intensity for each parameter was used, creating 27 rules. The center of gravity method was used to defuzzify the traffic density parameter. Based on the results, the designed algorithm was able to identify six different road images of different traffic states accurately.

Automated traffic violation apprehension system using genetic algorithm and artificial neural network

Developing countries face the problem of crowded and congested roads because of inefficient implementation of traffic rules. Motorists ignore the rules because they are not apprehended and can get away easily. This paper proposes an intelligent traffic system that is able to automatically detect and apprehend traffic violators, specifically motorists who either swerve or block the pedestrian lane. The system is designed by integrating three processes: violation detection, plate localization and plate recognition. The violation detection and plate localization were realized using genetic algorithm while the plate recognition process was performed using an artificial neural network. The recognition of the plate number is highly dependent on the position of the detected vehicle with respect to the camera. Thus, the recognized plate number will only be supplementary information about the violator; the physical attributes of the vehicle which is captured by the violation detection process will be the main information on the violator. Based on the results of 48 images tested, the overall system was able to detect the mentioned violations and to identify the plate number of the vehicles that were detected as traffic violators, with an average accuracy of 90.67%, and program runtime of 1.34 seconds.

Object locator and collector robotic arm using artificial neural networks

This paper suggests an artificial neural network approach to an object locator and picker. A robotic arm with two joints and a rotating base will function as a pick-and-place machine. The system follows the following constraints: (1) the base of the robotic arm will be situated at a predetermined and fixed position, hence limiting the area at which it can locate and pick an object and; (2) the object will be placed on a flat surface. The span of the robotic arm will determine this area. Also, it should be noted that the arms base and joints can move for limited angles only. The area of interest by the arm will be mapped into grids with coordinates. The inputs to the artificial neural network system will be the coordinates at which the object was positioned. Its outputs will be the angles of each joint of the robotic arm such that it can pick the object at its corresponding position.

Analog realization of a low-voltage two-order selectable fractional-order differentiator in a 0.35um CMOS technology

The analog realization of a selectable fractional-order differentiator (FOD) in a microelectronics scale is mainly the focus of this study. From this design, the order of differentiation can be selected between FOD(0.25) and FOD(0.50). While the aim is to make the hardware implementation as compact and small as possible, the authors employed reusability of resistors and capacitors when switching from one order to the other. The top-level schematic was generated using S-Edit while the physical layout implementation was outlined using L-Edit. The resulting integrated circuit (IC) design has a total chip area of 4.05mm × 3.10mm or equivalent to a final area of 12.56mm2. The whole chip is powered using dual supply voltage of only +0.75V Vdd and -0.75V Vss. Each order of differentiation was characterized in its magnitude and phase response in the working bandwidth from 10Hz to 1kHz.

Biomimetics in the design of a robotic exoskeleton for upper limb therapy

Current methodologies in designing robotic exoskeletons for upper limb therapy simplify the complex requirements of the human anatomy. As a result, such devices tend to compromise safety and biocompatibility with the intended user. However, a new design methodology uses biological analogues as inspiration to address these technical issues. This approach follows that of biomimetics, a design principle that uses the extraction and transfer of useful information from natural morphologies and processes to solve technical design issues. In this study, a biomimetic approach in the design of a 5-degree-of-freedom robotic exoskeleton for upper limb therapy was performed. A review of biomimetics was first discussed along with its current contribution to the design of rehabilitation robots. With a proposed methodological framework, the design for an upper limb robotic exoskeleton was generated using CATIA software. The design was inspired by the morphology of the bones and the muscle force transmission of the upper...

Audio multicast by Visible Light Communication for location information for the visually impaired

Visible Light Communication (VLC) is a new technology that may become an alternative choice for wireless communication in the future. The technology may be used in many indoor applications. The specific presentation of VLC in this study is with the use of light emitting diodes (LEDs) as the medium for transmission. Digital information will be sent through the LEDs as light pulses, and then a receiver will be able to collect the light pulses as a code and translate it to a corresponding audio data. In this study, the visible light communication system uses modulation schemes, such as on-off keying, so that the digital HIGHs and LOWs are representations of the binary code to be transmitted. Acknowledgement lights incorporated in the receiver are also utilized to make multicasting possible, and to signal that transmission is successful.

Full-custom design and characterization of a phase locked loop — DLS565 using 0.5um CMOS technology

The DLS565 is a Phase-locked loop (PLL) Integrated Circuit (IC) design project simulated on all process corner libraries (TT, FF, SS, FS, SF) using 0.5um CMOS technology. The final IC design layout of the PLL without bonding pads covers approximately 0.46mm × 0.5mm. The parameters of the DLS565 were measured and compared to the commercially available LM565C and NE565. It operates with a supply voltage of ±2.5 V with a maximum power dissipation of approximately 22 mW. DLS565 was able to capture frequencies as low as 15Hz and as high as 1.12MHz.