Jessie R. Balbin

Full-wave AC-DC converter in CMOS 0.18 micron for vibration electromagnetic energy harvest

This paper presents the design and implementation of full-wave AC-DC converter in 0.18 micron CMOS technology. Five sample voltages were taken from vibration electromagnetic harvester technology (VEHT) and simulated in three operating temperatures of 0, 25, and 70 degrees Celsius. The simulation results yielded: a maximum average power efficiency of 95.02% at 0°C 95.61% at 25°C, and 91.05% at 70°C; and an average regulation percentage of 10.45% at 0°C, 24.91% at 25°C, and 10.15% at 70°C.

Escherichia coli and Enterococcus faecalis growth detection device in ice using impedance microbiology and image processing technique

Various drinks served in different establishment always come with ice. Ice is the main component in preparing cold drinks- it also brings benefits to human health. However, due to poor sanitation in ice manufacturing, it can also put human health at risk. Escherichia coli and Enterococcus faecalis are the most common bacteria that surrounds the ice. Too much intake of contaminated ice caused by these two bacteria can lead to serious illness. On this study, the researchers presented a prototype that detects the growth of the bacteria, Escherichia coli and Enterococcus faecalis, using impedance microbiology and image processing. In addition, Graphic User Interface (GUI) was also be implemented in this study. GUI displays the captured images of the different phases of the sample and the concentration of bacteria present.

Microcontroller-based face recognition using combinations of morphing algorithms of Beier-Neely, Delaunay Triangulation and Alpha Blending

This study aims to compare three algorithms; the Beier-Neely Morphing Algorithm, the Delaunay Triangulation Technique, and the Alpha Blending, which can be used for face morphing with the intention of applying them on face recognition systems. The study showcases as well different integration of the said algorithms and based from the results, Alpha-Delaunay Triangulation is found out to be the best algorithm among the algorithm integrations.

Indexing and classifying snore characteristics using Support Vector Machine and integrated signal processing algorithm

Snoring is the loud or severe sound that buzzes when an individual sleep. Snoring can be produced through the nose, throat, uvula, or tongue. Each nature could be a sign that can be beneficial to specify what medical ailment or disorder a person could have. This paper focused on a sleeping disorder called Obstructive sleep apnea (OSA). Initiated from other investigation concerning about snoring detection and indexing, categories of snore have been segregated and classified from their elementary acoustic compositions such as the sound intensity and frequency. The study aims to come up with a device that records a snore sound that classifies the snore to what ailment the patient could be suffering using Support Vector Machine (SVM) and signal processing algorithm.

Crowd counting system by facial recognition using Histogram of Oriented Gradients, Completed Local Binary Pattern, Gray-Level Co-Occurrence Matrix and Unmanned Aerial Vehicle

A counting system is a device used for identifying the number of people present in a crowd. It has a wide variety of uses from fields of statistics, business and social sciences. This study introduces a method of a facial recognition counting system through the use of an unmanned aerial vehicle to capture aerial images of the crowd and the use of MATLAB to process those images to count the number of people present in the crowd. The algorithms used in this paper are Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) for low density and Gray Level Co-Occurrence Matrix (GLCM) for high density. From the data gathered, the program can classify an object as a head if it can see all of the human facial features like e.g. eyes, nose, mouth, etc. Thus, to obtain the best results in counting people in a crowd using this method, the user must take pictures at an angle and height where the features of the face can be seen, in our case, at 15 degrees and 3.2 meters respectively. But, if applied in an actual field, many people will be facing different directions and some faces will be blocked by other people.

Color vision deficiency compensation for Visual Processing Disorder using Hardy-Rand-Rittler test and color transformation

Visual processing skill is used to gather visual information from environment however, there are cases that Visual Processing Disorder (VPD) occurs. The so called visual figure-ground discrimination is a type of VPD where color is one of the factors that contributes on this type. In line with this, color plays a vital role in everyday living, but individuals that have limited and inaccurate color perception suffers from Color Vision Deficiency (CVD) and still not aware on their case. To resolve this case, this study focuses on the design of KULAY, a Head-Mounted Display (HMD) device that can assess whether a user has a CVD or not thru the standard Hardy-Rand-Rittler (HRR) test. This test uses pattern recognition in order to evaluate the user. In addition, color vision deficiency simulation and color correction thru color transformation is also a concern of this research. This will enable people with normal color vision to know how color vision deficient perceives and vice-versa. For the accuracy of the simulated HRR assessment, its results were validated thru an actual assessment done by a doctor. Moreover, for the preciseness of color transformation, Structural Similarity Index Method (SSIM) was used to compare the simulated CVD images and the color corrected images to other reference sources. The output of the simulated HRR assessment and color transformation shows very promising results indicating effectiveness and efficiency of the study. Thus, due to its form factor and portability, this device is beneficial in the field of medicine and technology.

Cloud storage based mobile assessment facility for patients with post-traumatic stress disorder using integrated signal processing algorithm

The research aims to build a tool in assessing patients for post-traumatic stress disorder or PTSD. The parameters used are heart rate, skin conductivity, and facial gestures. Facial gestures are recorded using OpenFace, an open-source face recognition program that uses facial action units in to track facial movements. Heart rate and skin conductivity is measured through sensors operated using Raspberry Pi. Results are stored in a database for easy and quick access. Databases to be used are uploaded to a cloud platform so that doctors have direct access to the data. This research aims to analyze these parameters and give accurate assessment of the patient.

Pattern recognition of concrete surface cracks and defects using integrated image processing algorithms

Pattern recognition of concrete surface crack defects is very important in determining stability of structure like building, roads or bridges. Surface crack is one of the subjects in inspection, diagnosis, and maintenance as well as life prediction for the safety of the structures. Traditionally determining defects and cracks on concrete surfaces are done manually by inspection. Moreover, any internal defects on the concrete would require destructive testing for detection. The researchers created an automated surface crack detection for concrete using image processing techniques including Hough transform, LoG weighted, Dilation, Grayscale, Canny Edge Detection and Haar Wavelet Transform. An automatic surface crack detection robot is designed to capture the concrete surface by sectoring method. Surface crack classification was done with the use of Haar trained cascade object detector that uses both positive samples and negative samples which proved that it is possible to effectively identify the surface crack defects.

Profiling and sorting Mangifera Indica morphology for quality attributes and grade standards using integrated image processing algorithms

Mango production is highly vital in the Philippines. It is very essential in the food industry as it is being used in markets and restaurants daily. The quality of mangoes can affect the income of a mango farmer, thus incorrect time of harvesting will result to loss of quality mangoes and income. Scientific farming is much needed nowadays together with new gadgets because wastage of mangoes increase annually due to uncouth quality. This research paper focuses on profiling and sorting of Mangifera Indica using image processing techniques and pattern recognition. The image of a mango is captured on a weekly basis from its early stage. In this study, the researchers monitor the growth and color transition of a mango for profiling purposes. Actual dimensions of the mango are determined through image conversion and determination of pixel and RGB values covered through MATLAB. A program is developed to determine the range of the maximum size of a standard ripe mango. Hue, light, saturation (HSL) correction is used in the filtering process to assure the exactness of RGB values of a mango subject. By pattern recognition technique, the program can determine if a mango is standard and ready to be exported.

Facial fluid synthesis for assessment of acne vulgaris using luminescent visualization system through optical imaging and integration of fluorescent imaging system

Acne vulgaris, commonly called as acne, is a skin problem that occurs when oil and dead skin cells clog up in a person’s pores. This is because hormones change which makes the skin oilier. The problem is people really do not know the real assessment of sensitivity of their skin in terms of fluid development on their faces that tends to develop acne vulgaris, thus having more complications. This research aims to assess Acne Vulgaris using luminescent visualization system through optical imaging and integration of image processing algorithms. Specifically, this research aims to design a prototype for facial fluid analysis using luminescent visualization system through optical imaging and integration of fluorescent imaging system, and to classify different facial fluids present in each person. Throughout the process, some structures and layers of the face will be excluded, leaving only a mapped facial structure with acne regions. Facial fluid regions are distinguished from the acne region as they are characterized differently.