Implementation of Size-Based Recognition on Automatic Liquid Filling Machine Using Canny-Edge Detection Method

liquid filling in small industries is often filled manually into containers, resulting in the liquid being poured into the container inaccurately, making it inefficient in cost and time. This paper proposes an edge detection method to automatically detect objects based on the size of 2 bottles for filling machines in soap liquid. The proposed process involves image processing stages using edge detection and filling machine control stages. The results showed that. The use of Dilated and Erode Image operations also helps to improve the detection and segmentation of 2 bottle sizes accurately. The detected bottle sizes are 10ml and 20ml, with 10ml being 5.4cm high and 2.0cm wide and 20ml being 7.7cm tall and 3.3cm wide. By examining the overall performance of the filling machine, this study proves that edge detection based on object size is a practical and essential approach in machine vision. The proposed edge detection method has great potential to improve the quality of segmentation and object detection in various image processing applications.