ICACT 2018
Permanent URI for this collectionhttp://repository.kln.ac.lk/handle/123456789/18944
Browse
2 results
Search Results
Item Smart Iron Rack: Image Processing Approach to Iron Clothes Remotely(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Yatanwala, Y.W.T.M.; Liyanaarachchi, D.S.G.L.D.Ironing process is a repeated manual task carried out by people daily. Conventional ironing methods always require significant amount of physical user interaction which is time consuming. As a solution, a research has been carried out to implement a smart iron rack with a mobile application that enables user to remotely perform the ironing process. As illustrated in figure below, the device connects with the mobile application through Wi-Fi and performs many tasks including hanger detection, wrinkle detection in cloths, identification of steam irons’ water levels and sending notifications to user. Iron rack consists of 5 hangers and a wide angle camera that moves along the horizontal beam to detect the clothes. When the user specifies a hanger number, the camera moves to the hanger position to check the availability of the cloth. Afterwards, the steam irons attached to the beam move vertically to iron the both sides of clothes. If the hanger number is not specified, the clothes on all five hangers will be ironed. The availability of the cloth on a particular hanger is detected using template matching algorithms in image processing. SIFT (scale-invariant feature transform) algorithm captures all interesting points of the hanger and shape of the hanger is taken as a key measure to decide the existence of the cloth. Raspberry-pi device which is mounted to micro controller, processes the images in order to determine the level of wrinkles in the outfit before and after the ironing process. “Grabcut” algorithm with localize Gaussian Mixture Model(GMM) is used to classify the foreground and background pixels in order to extract only the cloth from its background. Canny edge detection algorithm is used with (100,200) double thresholds to determine the number of wrinkle pixels in the cloth. The system was tested with 100 outfits made in cotton and silk materials. The accuracy of the system was tested in two stages. System could be able to achieve 0.80 F1 score for detecting clothes on hangers and 0.71 F1 score for detecting wrinkles in the clothes. “Smart iron rack” is a cost effective solution which is capable of remotely ironing 5 clothes at a time.Item Feature Extraction from Old Tamil Newspapers Using Histogram Minima(3rd International Conference on Advances in Computing and Technology (ICACT ‒ 2018), Faculty of Computing and Technology, University of Kelaniya, Sri Lanka., 2018) Kasthuri, S.; Darsha, M.; Ranathunga, L.Archaeological records which provide information about the history of human cultures and past events. Newspapers can be considered as one of the main sources of gathering archaeological data. It can be seen that there exist only a few numbers of systems for the processing of old Tamil newspaper articles. An automated image processing system proposed as a suitable solution to the way of efficient and flexible searching approach, which can be used for old Tamil newspapers. In this paper is presented image processing technique to extract the features such as headlines and sub-headlines from old Tamil newspaper scanned images. Historical newspapers become damaged over time. The images of these newspapers become difficult to read the contents. The quality of the image improved by preprocessing techniques such as grayscale dilation, median filtering, and adaptive binarization. It helps to easily extract needed information on the image. Segment the article and identify the heading of the article will help to improve data manipulation. Feature extraction from old Tamil newspaper images followed these step processes; Horizontal smoothing is necessary to distinguish the paragraphs and empty space between each column; Vertical smoothing is implemented to distinguish between each paragraph and headlines; Logical AND operation combines the outcome of horizontal smoothing and vertical smoothing using AND operation; Height measurement of each block is followed by horizontal projection, that involves scanning of pixels through horizontal arrays to measure the black pixel density against index of each row by using horizontal histogram minima. This step identified horizontals breaking points of individual regions within an article. The four major horizontal regions are headlines, sub-headline, text, and graphics. The irregular block may contain images within texts. Vertical projection can be carried out to distinguish the images among text. In the evaluation process used fifty articles which have different format of paragraph arrangements and also include images. First, identified and got the count of regions manually. After that compared the result from identified regions and got the measurements. The region was identified with articles in the efficiency of 80.09%, headline extraction accuracy was 81.616%.