Research Publications Authored by SLIIT Staff

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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.

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Subject: search.filters.subject.OpenCV

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    PublicationEmbargo
    OMNISCIENT: A Branch Monitoring System for Large-scale Organizations
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Jayasekara, T.; Omalka, K.; Hewawelengoda, P.; Kanishka, C.; Samarasinghe, P.; Weerasinghe, L.
    Omniscient is a system that enables higher-level management of massive organizations to remotely monitor and scrutinize the activities that take place in the branches from the head office itself by providing exclusive insight in the form of detailed reports on the employees’ behaviour and performance daily, weekly and monthly. The system further monitors the branch and provides reports on any suspicious behaviour and also on the customers’ activity within the branch premises. Omniscient rates the customer’s level of satisfaction by capturing the customer’s facial expressions and analyzing their emotions while they are being served. The employee face and dress recognition models have accuracies of 90.90% and 87.00% respectively while, employee activity detection has an accuracy of 89.00%. Customer emotion and miscellaneous activities detection models have the accuracies of 91.50% and 83.00% respectively. All of the aforementioned procedures were made possible by systematically analyzing the IP camera video footage obtained throughout the day to analyze the work productivity and performance of the branch as accurately as possible using deep learning and modern visual computing techniques like CNN, OpenCV, Haar Cascade classifier, face recognition, Dlib and Darknet.
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    PublicationEmbargo
    Smart Office Automation System for Covid Prevention
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Rajapaksha, R.A.D.S.; Costa, L.S.; Prasanna, P.L.U.S.C.; Disanayaka, A.P.D.; Senarathne, A. N.; Wijekoon, Janaka L.
    Today, this coronavirus is spread all around the world. Most organizations and businesses start to think about how to continue their business in a situation like COVID-19 and their employees’ health and business security. To avoid and be safe from this type of disease, there are some common rules to follow. Keeping a distance, wearing a mask, cleaning our hands, are some health guidelines from them. According to the current situation, many inventors are trying and have already given some solutions to avoid these kinds of situations aligning with health guidance’ provided by WHO. With the advantage of advanced modern-day technologies and ideas, researchers started to think about how to face situations like these with the new technologies and found that many users are highly interested and motivated with automated systems. Thus, from this study, we aim to provide a fully automated office management system to prevent corona with advanced technology in combination with IoT technologies, Machine learning, Cloud technologies, and sensor technologies. Considering the security aspect, Controlling the main entrance, identifying, ensuring user’s authentication before entering the building, and monitoring employee activities are very significant aspects of the study. As the result of the study, the combination of IoT technologies and Machine Learning with deep learning mechanisms have guaranteed organizational business continuity, employees' health, and security.
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    PublicationOpen Access
    IMAGE PROCESSING BASED GIRTH MONITORING AND RECORDING SYSTEM FOR RUBBER PLANTATIONS
    (Academy & Industry Research Collaboration Center (AIRCC), 2015-02-01) Thilakarathne, C; Bhanusri, P; Randeny, T; Rupasinghe, H; Kulasekere, E. C
    Measuring the girth and continuous monitoring of the increase in girth is one of the most important processes in rubber plantations since identification of girth deficiencies would enable planters to take corrective actions to ensure a good yield from the plantation. This research paper presents an image processing based girth measurement & recording system that can replace existing manual process in an efficient and economical manner. The system uses a digital image of the tree which uses the current number drawn on the tree to identify the tree number & its width. The image is threshold first & then filtered out using several filtering criterion to identify possible candidates for numbers. Identified blobs are then fed to the Tesseract OCR for number recognition. Threshold image is then filtered again with different criterion to segment out the black strip drawn on the tree which is then used to calculate the width of the tree using calibration parameters. Once the tree number is identified & width is calculated the girth the measured girth of the tree is stored in the data base under the identified tree number. The results obtained from the system indicated significant improvement in efficiency & economy for main plantations. As future developments we are proposing a standard commercial system for girth measurement using standardized 2D Bar Codes as tree identifiers