Research Papers - Dept of Computer Systems Engineering

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Subject: search.filters.subject.Image Processing

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Now showing 1 - 7 of 7
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    tAssessee: Automatically Assessing Quality of Tea Leaves using Image Processing Techniques
    (IEEE, 2022-11-30) Sivalingam, J; Sivachandrabose, L.N; Loganathan, M; Sivakumaran, J; Panchendrarajan, R
    Sri Lanka is one of the well-known international’s pinnacle tea exporters with a high global demand attracting millions of foreign exchanges, which strengthens the economy of the country. Despite the fact that tea brings a good source of foreign exchange, the tea industry lacks efficiency and effectiveness during the assessment of plucked tea leaves which compromises the significant quality of tea. While studies have revealed various factors affecting the tea quality, key factors are identified as the presence of tea diseases, pest attacks, the mixture of fresh and mature tea leaves, and the mixture of tea grades present in the tea sack. In this paper, we focus on automatically assessing the quality of tea leaves for a single tea leaf and bulk tea leaves before initiating the tea manufacturing process. The proposed tAssessee system allows the user to upload the image of a single tea leaf or bulk tea leaves to automatically assess four different quality factors of tea leaves such as disease, pest attack, freshness, and grade using Convolutional Neural Network based models and using various image processing techniques. This will assist the tea supervisors in the tea factories to automatically assess the quality of tea leaves where the manufacturing process can be segregated according to the quality of tea leaves and determine the pricing accordingly. Extensive experiments performed using the tea leaves images gathered in tea factories reveal, that the proposed tAssessee system can assess the quality of single tea leaf and bulk tea leaves with the accuracy range of 87% - 98% and 91% - 100% respectively.
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    Smart Platform for Film Shooting Management
    (IEEE, 2019-12-06) Senarath, S. M. M. M; Perera, M. T. K; Viduranga, D. G. R; Wijayananda, H. M. C. S; Rankothge, W
    Producing a movie involves difficult and time-consuming phases, specially, pre-production and production. It's a challenging task to find out suitable locations for each scene and building a schedule without any clashes. We have proposed and implemented a platform for film shooting management with following modules: (1) identify required background for each scene, (2) classify available film shooting locations, (3) compare the required background and available film shooting locations and (4) schedule the shooting of each scene. We have used natural language processing, image processing, string matching algorithms and optimization techniques to implement the above-mentioned modules. Our results show that, using our proposed modules, the film shooting management related services can be automated efficiently and effectively.
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    PublicationOpen Access
    BIOMETRIC SMART SECURITY SYSTEM WITH CHILD CARE FOR A SMART SOCIETY
    (IET- Sri Lanka Network, 2019) Lokuliyana, S; Mundigala, I. U; Sanjeewa, G. H. A
    This research is mainly focused on Infant movement detection and alerting, in order to enhance their security within the home premises. As the first move, the research focuses on the identification of the human and classifying whether an adult or a baby. Then a model was built up in three classifications to identify static and dynamic positions of the infant, through Image Processing and analysis. In order to enhance the accuracy of the custom classifiers an already trained model using 1 million image set was retrained by customized image sets. To present this research as a smart home solution modern technology were used in implementing the close connection between the infant and the parent.
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    CURETO: Skin Diseases Detection Using Image Processing And CNN
    (IEEE, 2020-11-17) Karunanayake, R. K. M. S. K; Dananjaya, W. G. M; Peiris, M. S. Y; Gunatileka, B. R. I. S; Lokuliyana, S; Kuruppu, A
    Busy lifestyles these days have led people to forget to drink water regularly which results in inadequate hydration and oily skin, oily skin has become one of the main factors for Acne vulgaris. Acne vulgaris, particularly on the face, greatly affects a person's social, mental wellbeing and personal satisfaction for teens. Besides the fact that acne is well known as an inflammatory disorder, it was reported to have caused serious long-term consequences such as depression, scarring, mental illness, including pain and suicide. In this research work, a smartphone-based expert system namely “Cureto” is implemented using a hybrid approach i.e. using deep convolutional neural network (CNN) and natural language processing (NLP). The proposed work is designed, implemented and tested to classify Acne density, skin sensitivity and to identify the specific acne subtypes namely whiteheads, blackheads, papules, pustules, nodules and cysts. The proposed work not only classifies Acne Vulgaris but also recommends appropriate treatments based on their classification, severity and other demographic factors such as age, gender, etc. The results obtained show that for Acne type classification the accuracy ranges from 90%-95% and for Skin Sensitivity and Acne density the accuracy ranges from 93%-96%.
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    Real-Time Greenhouse Environmental Conditions Optimization Using Neural Network and Image Processing
    (IEEE, 2020-11-04) Wickramaarachchi, P; Balasooriya, N; Welipenne, L; Gunasekara, S; Jayakody, A
    Agricultural business is one of the biggest areas in world economy. With the growth of population losing agricultural lands is the major issue in world food production. Therefore, controlled environment agricultural systems under vertical farming have been introduced with greenhouses. Within greenhouses there is not a mechanism to continuously monitor the growing community and change the climate conditions. Existing systems only predict the required conditions for the plant and once predicted that value is provided to the plants continuously or change the values from season to season. To address these issues, a working prototype of an IoT based smart hydroponic system is introduced, which uses computer vision to gain maximum profits by growing a specific cultivation by providing endemic environmental conditions and addressing the problems over its growing process. There, this research presents a way of external environmental condition optimization. Regression type Feed Forward Neural Network is considered for this research to optimize the required conditions for tomato plants. Based on the current height of the plant, expected height for next 24 hours, and growth date of the plants neural networks predict the CO2, temperature and humidity level for next 24 hours with the accuracy of 88.33%, 89.21% and 92.65% respectively. The objectives of the research can be achieved by this retrieved results. The successful implementation of neural networks results a cost-effective modern farming solution for growers. This research will be supportive to attain a fundamental comprehension on the concept of the research area.
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    “iParking” – Smart way to Automate the Management of the Parking System for a Smart City
    (2020 2nd International Conference on Advancements in Computing (ICAC), SLIIT, 2020-12-10) Jayakody, J.A.D.C. A.; Karunanayake, S.A.H.M.; Ekanayake, E.M.C.S.; Dikkubura, H.K.T.M.; Bandara, L.A.I.M.
    An efficient and effective smart outdoor parking system is a crucial need with the rapid development of the economy and the improvement of smart city modernization level, traffic and parking have become serious problems due to the explosive growth of the capital number of vehicles. This research will propose proper management for outdoor parking issues with an efficient solution for parking slots availability and occupancy detection using a classification approach and providing real time environment positioning accurate enhancement approach for global positioning system using map matching algorithm to classify vehicle direction on the road with the high precision location. The image processing technology is used to identify a vehicle's license plate and activate access control systems for automatic gate access to authorized members. The proposed system can provide information on promotions for a target audience on a screen where all consumers can view while using the parking facility with the use of machine learning algorithms, this will help to enhance the market value of the proposed system.
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    Smart Harvesting based on Image Processing
    (IEEE, 2020-12-17) Joseph, s. p; Wijerathna, L. L. M. C; Epa, K. G. R. D; Egalla, E. K. W. A. P. K; Abeygunawardhana, P. K. W
    Vision device is a critical component of fruit harvesting mobile robot which is designed for recognizing and harvesting of tomato fruits. The system of vision device of the moving robot, for a dedicated path identification with the use of colour detection algorithms and contour detection algorithms could be stated as an additional usage of the image-based technology. When the robot operates in real life, varying environmental parameters would not affect its activity, since the robot will be functioning mainly indoors, specifically in a greenhouse. Robust fruit segmentation algorithms for the visual system and the fruit plucking mechanism using a readymade robot arm with a soft gripper where it operates with basic hardware components like motors, controlled by a microcontroller with the intervention of kinematic theories, is being used with the goal of collecting fruit objects efficiently in the natural world. Plucking only the ripe and healthy object fruit without damaging both the fruit and the tree is the intended task of the system. The aim is to reduce human effort by promoting automation concepts in agriculture in developing countries like Sri Lanka with great potential, where agriculture plays a vital role in the development of the economy while indoor plantation and harvesting mechanism are also being developing to cater to the economy of the country as well. The way that this system is implemented will be discussed in this paper.