[AI Image Inspection Case] Part Identification
We will evaluate parts such as washers and screws using AI image inspection software!
It seems that there are many washers and similar screws used in various industries, making it often cumbersome to distinguish between them. This time, we received an inquiry about how to differentiate washers and screws. Since this is a common issue, we have also created a video to make it easier to visualize. Please take a look for reference. "Discovering the simultaneous omission of two types of parts and stopping the conveyor" https://skylogiq.co.jp/DIY_HowTo/368 【Inspection Settings and Results】 We enclosed the target areas we wanted to detect with a frame and labeled them by type. In this verification, we focused on six types of parts to examine the feasibility of differentiation. We believe that false detections and non-detections occurred due to insufficient training data for the patterns in which the target objects appeared in the images, and we expect that simply increasing the patterns in the training data will improve detection accuracy. However, we cannot determine the final rate of false detections or non-detections until we actually conduct the training.
basic information
【Software and Equipment Used】 Software Used: DeepSky Field of View: Approximately 41 x 32 mm Minimum Size of Inspection Target: 2 mm Number of Inspection Points: 1 location, distinguishing parts from the entire screen Camera Resolution: 1.3 million pixels Lens Focal Length: 25 mm Distance Between Lens and Product: Approximately 190 mm
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