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    Electronic Parts Counting in Physics Laboratory Using Difference of Gaussians Edge Extraction
    (2024-01-01)
    Leelawattananon, Tanaporn
    ;
    Chittayasothorn, Suphamit
    Small electronic parts counting in the physics laboratory is a challenging task. These small objects such as resistors, capacitors, and inductors are used in physics laboratories and because of their numbers and small size, are hard to count in a short period of time. The precise inventory of these small electronics parts is therefore compromised. In this paper we present the development of a small electronics parts counting system. The system employs object edges detection using the difference of gaussian operator. This technique is suitable for those small electronic objects which have clear boundaries. By adjusting relevant parameters sigma and threshold to suit the size of the objects, the edge images are clearly detected thus enable correct counting of the objects which leads to correct inventory of electronics parts. An alternative technique using the canny edge detector operator is also used as a comparison technique. The experimental results are precise.
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    Measuring icon recognization mapping with automated decision making system
    (2019-07-01)
    Tangtisanon, Pikulkaew
    ;
    Khongtrakan, Yanaphat
    Nowadays, mobile technology has been rapidly improved in both hardware and software aspects. Thus, many applications have been built and install in a smartphone. To find an application in the smartphone, a user has to search through various icons that design based on functions of the application. The purpose of this research is to build an automatic system that helps software designers to decide if the designed-icon is a proper icon that could be recognized by the user easily or not using entropy, Canny edge detection, and decision tree. Two experiments are reported in this research. 100 icons in both Android and iPhone operation system were used in both experiments. The sample included undergraduate students and workers in Thailand (n=90) ages ranged from 18 to 57. The first experiment was made in order to find a relationship among edge, entropy and human visual processing and use it as a training and testing dataset for the proposed system. The second experiment shows that the proposed system can be used to judge for a proper icon property with 73.33% accuracy rate.