Eye Blink Classification for Assisting Disability to Communicate Using Bagging and Boosting

Disability is a physical or mental impairment. People with disability have more barriers to do certain activity than those without disability. Moreover, several conditions make them having difficulty to communicate with other people. Currently, researchers have helped people with disabilities by developing brain-computer interface (BCI) technology, which uses artifact on electroencephalograph (EEG) as a communication tool using blinks. Research on eye blinks has only focused on the threshold and peak amplitude, while the difference in how many blinks can be detected using peak amplitude has not been the focus yet. This study used primary data taken using a Muse headband on 15 subjects. This data was used as a dataset classified using bagging (random forest) and boosting (XGBoost) methods with python; 80% of the data was allocated for learning and 20% was for testing. The classified data was divided into ten times of testing, which were then averaged. The number of eye blinks’ classification results showed that the accuracy value using random forest was 77.55%, and the accuracy result with the XGBoost method was 90.39%. The result suggests that the experimental model is successful and can be used as a reference for making applications that help people to communicate by differentiating the number of eye blinks. This research focused on developing the number of eye blinks. However, in this study, only three blinking were used so that further research could increase these number

Analysis of Segmentation Parameters Effect towards Parallel Processing Time on Fuzzy C Means Algorithm

Fuzzy C Means algorithm or FCM is one of many clustering algorithms that has better accuracy to solve problems related to segmentation. Its application is almost in every aspects of life and many disciplines of science. However, this algorithm has some shortcomings, one of them is the large amount of processing time consumption. This research conducted mainly to do an analysis about the effect of segmentation parameters towards processing time in sequential and parallel. The other goal is to reduce the processing time of segmentation process using parallel approach. Parallel processing applied on Nvidia GeForce GT540M GPU using CUDA v8.0 framework. The experiment conducted on natural RGB color image sized 256x256 and 512x512. The settings of segmentation parameter values were done as follows, weight in range (2-3), number of iteration (50-150), number of cluster (2-8), and error tolerance or epsilon (0.1 – 1e-06). The results obtained by this research as follows, parallel processing time is faster 4.5 times than sequential time with similarity level of image segmentations generated both of processing types is 100%. The influence of segmentation parameter values towards processing times in sequential and parallel can be concluded as follows, the greater value of weight parameter then the sequential processing time becomes short, however it has no effects on parallel processing time. For iteration and cluster parameters, the greater their values will make processing time consuming in sequential and parallel become large. Meanwhile the epsilon parameter has no effect or has an unpredictable tendency on both of processing time

Prototype of Student Attendance Application Based on Face Recognition Using Eigenface Algorithm

Prototype of face recognition based attendance application that has been developed to overcome weaknesses in DTETI UGM student manual attendance system has several weaknesses. These weaknesses are a decrease in facial recognition accuracy when operating under conditions of varying environmental light intensity and in condition of face rotating towards z axis rotation centre. In addition, application prototype also does not yet have a database to store attendance results. In this paper, a new application prototype has been developed using Eigenface face detection and recognition algorithm and Haar-based Cascade Classifier. Meanwhile, to overcome prototype performance weaknesses of the previously developed application, a pre-processing method was proposed in another study was added. Processes in the method were geometry transformation, histogram levelling separately, image smoothing using bilateral filtering, and elliptical masking. The test results showed that in the category of various environmental light intensity conditions, face recognition accuracy from developed application prototypes was 16.71% better than previous application prototypes. Meanwhile, in category of face slope conditions at z axis rotation centre, face recognition accuracy from developed application prototype was 38.47% better. Attendance database system was also successfully implemented and running without error

A Novel User Experience Study of Parallax Scrolling using Eye Tracking and User Experience Questionnaire

Parallax scrolling technique is being devoted as a unique and an innovative trend in the web design. Parallax scrolling provides 3D perception on a web page. Previous works observed user experience issues of parallax scrolling merely based on subjective questionnaires. Their findings leave a research question whether the results are valid as a written questionnaire may be perceived differently by participants. Additionally, bias and ambiguity in the questionnaire can affect the research results significantly. To solve this research problem, we present a novel user experience study of parallax scrolling in storytelling and online shop website using eye tracking and User Experience Questionnaire (UEQ). Forty (N=40) participant joined the experiment on a voluntary basis. Each participant only interacted with one out of two websites (storytelling or online shop) and only one effect (with or without parallax scrolling). We found that parallax scrolling affected UEQ score of Attractiveness of the storytelling website (p < 0.05). Our findings suggest that parallax scrolling improves user engagement in storytelling website. We also observed that the participants spent time almost two times faster to find an object of interest in an online shop with parallax scrolling compared with the similar task in an online shop without parallax scrolling (p < 0.05). We thus argue that parallax scrolling is useful during interacting with particular websites that require visual object localization. In future, web designers should consider the appropriate usage of parallax scrolling to optimize user experience while avoiding additional distraction caused by this technique

A New Native Video Filtering based on OpenGL ES for Mobile Platform

In the last five years, there have been many Android applications implementing video filter or video effect as an excellent feature. Open CV is an open source computer vision library that can be simply and easily used for video filtering in Android application. However, using OpenCV library for video filtering commonly yields a bigger size of Android application. The concept of “Develop for Billion People” has enforced the developers to optimize the size of their applications to preserve resources and size of memory—as not all Android devices come with sufficiently large memory. On the other hand, OpenGL ES does not burden the filtering process because of its smaller size when it is implemented during the application development. In this research, we present a new native video processing technique using OpenGL ES. We implement the proposed method on a native video file without decreasing its quality before video filtering process. The experiments were conducted with five different mobile devices. We compared several metrics including: quality of the resulted video, file size of the apk, power consumption, and memory usage. Based on the experimental results, OpenGL ES produces smaller file size of apk (2 MB) compared with the produced file size of apk by Open CV (20MB). The resulted file after video filtering possesses same properties as observed before video filtering. Additionally, OpenGL ES uses more efficient power with 0.1965 mAh, while OpenCV consumes 0.283 mAh. Finally, video filtering with OpenGL ES uses 29.3% lesser memory than video filtering with OpenCV. The proposed method is proven to be more appropriate with “Develop for Billion People” as it preserves more computational resources compared with the existing video filtering technique in Android

Virtual Reality-based Platformer Games Development for Elevating Architectural Heritage Awareness

As a country with abundant traditional culture, Indonesia is facing serious challenge in conserving them. There is a need to promote the traditional culture to a wider area of people, particularly to the younger generation. Virtual world offers a new way of promoting a nation’s culture via Virtual Reality (VR). This research aims to develop a VR-based platformer mobile game to promote cultural awareness in a new and creative way for younger generation. In the game, a player can observe one famous architectural heritage in Yogyakarta—Mesjid Gedhe Kauman—in fun way of game. A survey is conducted to measure its success in reaching the predetermined goals and to measure its user experience (UX). The survey confirm that the VR-based platformer game helps them in learning cultural value of the architecture (62.5/100) and it is relatively easy to navigate (72.5/100). Moreover, it has a good user experience (UX) score—all are above 0.8, meaning that its users are generally comfortable in playing the game

Detection of malaria parasites in thick blood smear: A review

Based on data from World Health Organization, in 2015, there are 90% of deaths caused by malaria disease in Africa, Southeast Asia and countries of eastern Mediterranean. It makes the malaria become one of the most dangerous diseases that often leads to death. To support the diagnosis of malaria, early detection of plasmodium parasite is needed. Recently, malaria diagnosis process can be done with the help of computer, or often referred to as Computer Aided Diagnosis (CAD). By utilizing the digital image from the blood staining process, digital image processing can be performed to detect the presence of malaria parasite. There are 2 types of blood smear images that can be used in the malaria diagnosis process, namely, thin blood smear images and thick blood smear images. This paper provides a review of the techniques and methods used in the diagnosis of computer-assisted malaria using thick blood smear images as a diagnostic material

Wart treatment method selection using AdaBoost with random forests as a weak learner

Selection of wart treatment method using machine learning is being a concern to researchers. Machine learning is expected to select the treatment of warts such as cryotherapy and immunotherapy to patients appropriately. In this study, the data used were cryotherapy and immunotherapy datasets. This study aims to improve the accuracy of wart treatment selection with machine learning. Previously, there are several algorithms have been proposed which were able to provide good accuracy in this case. However, the existing results still need improvement to achieve better level of accuracy so that treatment selection can satisfy the patients. The purpose of this study is to increase the accuracy by improving the performance of weak learner algorithm of ensemble machine learning. AdaBoost is used in this study as a strong learner and Random Forest (RF) is used as a weak learner. Furthermore, stratified 10-fold cross validation is used to evaluate the proposed algorithm. The experimental results show accuracy of 96.6% and 91.1% in cryotherapy and immunotherapy respectively

Research on Skewed License Plate Recognition: A Systematic Literature Review

A plate recognition system is an application of computer vision technologies for detecting and recognizing vehicle license plates. Several disturbances cause the system to be inaccurate in detecting and recognizing vehicle license plates. One of several disturbances is perspective distortion due to image taking with an incorrect camera angle. This distortion causes the captured license plate to be bent from its actual shape. In order to overcome perspective distortion, a variety of techniques have been developed to increase the plate recognitions system's ability. However, to the authors' best knowledge, there is no review paper that discusses various studies on handling perspective distortion in plate recognition systems. Here we present a systematic literature review to help researchers in addressing the recognition of skewed license plates. This study compares several studies published between 2015 and 2020 on plate recognition techniques, especially those related to skewed license plate recognition. The search process was conducted on databases of research literatures and resulted in 25 primary studies. This paper also identifies various datasets and methods to obtain a comprehensive understanding as a reference in developing the plate recognition algorithm. © 2021 IEEE

Similarity Measures of Object Selection in Interactive Applications based on Smooth Pursuit Eye Movements

Gaze-based interaction in various digital technologies is a rapidly growing research area. Eye tracking provides an alternative input modality to control interactive contents in computers. Nowadays, eye tracking is not only expected to be a personal assistive technology, but also to be a controller for interactive contents in a public display. Instead of fixational eye movement, smooth pursuit eye movement has been used for object selection in gaze-based interactive applications. However, previous works did not consider various similarity measures for spontaneous object selection. Hence, no information on how different similarity measures affect performance of object selection. To fill this gap, we compared two similarity measures—Euclidean distance and Pearson’s product moment coefficient— for object selection. We presented simple interactive applications containing four dynamic objects, each of which was presented subsequently or simultaneously. The participants were asked to select the objects by gazing and following the trajectory of the moving objects. Our results show that object selection with Euclidean distance achieved superior accuracy (78.65%) compared with object selection with Pearson’s product moment coefficient (57.38%). In future, our results maybe used as a guideline for development of spontaneous gaze-based interactive application