Measuring Icon Recognization Mapping with Automated Decision Making System

2019 5th International Conference on Engineering, Applied Sciences and Technology (ICEAST) Pub Date : 2019-07-02 DOI:10.1109/ICEAST.2019.8802576

Pikulkaew Tangtisanon, Yanaphat Khongtrakan

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Abstract

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 ($\mathbf{n}=90$) 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.

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用自动决策系统测量图标识别映射

如今，移动技术在硬件和软件方面都得到了迅速的发展。因此，许多应用程序已经被构建并安装在智能手机中。为了在智能手机中找到应用程序，用户必须搜索根据应用程序功能设计的各种图标。本研究的目的是利用熵、Canny边缘检测和决策树，建立一个自动系统，帮助软件设计者判断所设计的图标是否是用户容易识别的合适图标。本研究报告了两个实验。两个实验都使用了Android和iPhone操作系统中的100个图标。样本包括泰国的本科生和工人($\mathbf{n}=90$)，年龄从18岁到57岁不等。第一个实验是为了找到边缘、熵和人类视觉处理之间的关系，并将其作为所提出系统的训练和测试数据集。第二次实验表明，该系统可用于判断合适的图标属性，准确率为73.33%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 5th International Conference on Engineering, Applied Sciences and Technology (ICEAST)

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