Research Papers - Dept of Software Engineering

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/1022

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Subject: search.filters.subject.Image Processing

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Now showing 1 - 5 of 5
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    Interactive Game Application for Garbage Disposal using Image Processing and Location Based Services
    (IEEE, 2018-12-21) Nanayakkara, P; Rathnaweera, T; Weerasingha, S; Pieris, Y
    Waste disposal is one of the major contemporary topics which is being discussed globally. The main reason for this issue to have such prominence is due to the fact that people are not aware how far-reaching this topic has become. In this paper we propose ScrapWrap, an interactive game for garbage disposal where the main objective is to make people aware how imperative it is to dispose garbage and assist people to have a change of attitude towards this complication. In Scrapwrap, people will be awarded considering several facts such as for notifying littered areas, for cleaning the area, for verifying the cleaned area, and for arranging cleaning campaigns. A chat-based community is created within ScrapWrap so that players could interact with each other, and this strategy is useful when arranging campaigns or scavenger hunt activities to clean the waste. An assistive chat bot is introduced to solve the problems a player might have, and to remind the event details and guide the player throughout the game flawlessly. The long-term goal of introducing Scrapwrap is to let people be aware of the importance of garbage disposal in an interactive manner and to improve the cleanliness of the surroundings.
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    DFOG-Image Processing Application for Real-Time Defogging
    (IEEE, 2020-11-04) Indiketiya, I. H. O. H; Kulasekara, K. M. R. A; Thomas, J. M; Gamage, I; Thilakarathna, T
    The enhancement of real-time video taken under bad visibility or bad weather is a vital necessity in consumer transport industry and computer vision applications. During the past decade, many researchers have been devoted to the problem of how to remove fog noise from real-time video. Nowadays vehicle industry uses various computing systems to assist in the transport of travelers from one location to another .now most of the cars have revers camera front cameras and sensors who give the signal when the vehicle is near to another object. These detections and identification are useful for the safe operation of vehicles. When looking through vehicle accident history, many accidents caused bad weather conditions. Fog, haze, rain, and other natural weather conditions cannot remove physically. Fog and haze block vison above 1 kilometer. There is a defogger in the windscreen, but it is only removed Mist on the windscreen. For the driver's vision above the rode, there is no such thing for that. The purpose of this research paper is introducing a new system to remove fog from real-time video and give detailed visual to the driver in foggy or other bad weather condition. This D-Fog system includes functions such as give clear realtime visual in bad weather condition, recognize, and give details about the object above the road, give the distance between objects and vehicle. In this system, main function is producing real-time defogged, clear video. Combination of Ha and Hoon method and Dark channel priority method used to get this real-time defog video. To recognize the object, this system has use thermal sensors and heat maps. To get the distance between object and vehicle this system has use LIDAR sensors. Because of this facility, we can name this system as three in one system.
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    PublicationOpen Access
    A mobile base application for cataract and conjunctivitis detection
    (University of Kelaniya, 2020) Soysa, A; De Silva, D. I
    With time the life patterns of humans have evolved at a rapid space. Today, it has come to a point where people are opting to put their health status behind other priorities in life. A contemporary example is the spreading of the COVID-19 virus. One of the other significant health issues faced by the present-day community is illnesses related to the eyes. However, unlike other health issues, most of the eye diseases can be cured with proper attention. Cataract and Conjunctivitis are identified as two of the main eye diseases faced by a mass amount of people around the world. If left untreated, these diseases can even lead to blindness. As a matter of fact, Cataract has been reported as the first cause of blindness by the world health organization. Typically, the detection of these diseases is done by an ophthalmologist with the use of a special medical equipment. Thus, the channeling of an ophthalmologist has become a mandatory requirement for the detection of these diseases. In addition, the availability of medical equipment and medical officers is deficient in rural areas. Thus, as a solution for the above-mentioned issues, it was decided to propose a mobilebased application, Eye Plus, for the detection of Cataract and Conjunctivitis diseases. Using Eye Plus, one would be able to test his/her eyes at a convenient time in any place for a zero cost. In addition, it provides additional information related to Cataract and Conjunctivitis diseases. Another special feature of the application is the ability to operate it without the help of another party. At present, the application achieved a success rate of 83.3% for a collection of 150 images.
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    Virtual Dressing Room: Smart Approach to Select and Buy Clothes
    (2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT, 2021-12-09) Weerasinghe, S.W.P.N.M.; Rajapaksha, R.M.D.D.; Sathsara, L.G.I.; Gunasekara, H.S.D.N.; Wijendra, D.R.; De Silva, D.I.
    The clothing industry portrays a major part of a respective country`s economy. Due to the predilection for clothing items of the people have led to the increasing of physical and online clothing stores in all around the world. Most of the people are used to go to the physical shopping and purchase their desired clothing items. But, as a consequence of the current pandemic situation, most of the people are unable to step out from their homes. This application is intended to cater an opportunity to the customers, who are not able to reach the physical clothing stores due to a pandemic situation and mobility difficulties. In addition, this application diminishes the time wastage, clothing size mismatches and the lesser user satisfaction ratio inside a physical clothing store. A customized 3D model has featured in the application to cater the virtual fitting experience to the customer. And the AI chatbot assistant in the application interacts with the user while catering virtual assistance for a better cloth selection process. In addition to that, this application has concentrated on the clothing shop by providing a future sales prediction component utilizing the K-Nearest Neighbors algorithm to provide an aid to their business commitments.
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    Predicting Diabetes Mellitus Using Machine Learning and Optical Character Recognition
    (IEEE, 2021-04-02) Silva, W. A. J. R; Shirantha, H. M. K; Balalla, L. J. M. V. N; Ranasinghe, R. A. D. V. K; Kuruwitaarachchi, N; Kasthurirathna, D
    Diabetes Mellitus is recognized as a chronic metabolic disease that is characterized by hyperglycemia. As stated by the International Diabetes Federation, the statistics reveal that the incidence of diabetes among adults in Sri Lanka is 8.5%. In hindsight, this indicates that an average of one in every twelve adults in Sri Lanka is at risk of being diagnosed with the disease. However, presently, due to the lack of knowledge or mediums concerning the disease and its symptoms, diabetes often goes undetected which has resulted in 1/3 rd of the constituent population being unaware that they possess the disease. The proposed system aims to implement an application to read and analyze medical reports which will generate data that predicts the probabilities of the contraction and onset of diabetes, with insurance of maximum system efficiency and data credibility. Machine learning classification algorithms and optimization techniques have been used to predict diabetes status with maximum accuracy. To extract data from medical reports Optical Character Recognition, Image Processing, and Natural Language Processing have been used