Basic Study on Facial Oil Blotting Paper Counting Using a Webcam
Junya Sato, Toru Koide, Yuki Kisi, Takayoshi Yamada, Kazuaki Sibata, Kazuaki Ito, Takuya Akashi · 2018
Currently, racial oil blotting papers are counted by hand. However, it takes a long time and this is hard work. Hence, an automatic counting system is necessary. In order to achieve this, we developed a cheap system using a webcam. This system firstly captures one image of arranged papers by shifting. Secondly, the paper boundaries are obtained as straight lines by utilizing the proposed image processing. By counting the acquired lines, the system outputs the number of papers. However, the captured image has noises such as the change of illumination and shadows. They make the extraction of the accurate boundaries difficult. For the accurate extraction, optimal parameters of the image processing must be set. Since the prediction of the optimal parameters in advance is difficult, the proposed method adopts genetic algorithm (GA). Also, Hough transformation for the straight line detection is improved. By applying the proposed method, the accurate paper counting is possible. For the experiment, 14 images were captured in various environments using a general webcam. Then, the proposed method was compared to a latest related work. As a result, F-measure of each method was 0.995 and 0.945.