System and method for generating training image data for supervised machine learning, and non-transitory recording medium

A method for generating training image data for supervised machine learning for training a defect classifier to be applied to visual inspection, the method comprising:

• arbitrarily selecting a defect model from defect models obtained by modeling shapes and optical characteristics of defects and stored on a defect model storage;
• arbitrarily selecting an inspection target surface model from inspection target surface models obtained by modeling shapes and optical characteristics of inspection target surfaces and stored on an inspection target surface model storage;
• and
• arranging the selected defect model and the selected inspection target surface model in any space in which ray tracing is performed by ray tracing simulation software in which an illumination optical system, an image pickup optical system, and an imaging sensor including a plurality of pixels are modeled, tracing a plurality of light rays, calculating illuminance at each of the pixels based on an intensity and a number of light rays entering the pixels, and generating pseudo image data as the training image data based on the calculated illuminance,
• generating the pseudo image data while at least one of an illumination optical system model or a model obtained by synthesizing the defect model and the inspection target surface model is moved by a minute amount and arranged at a plurality of different positions,
• wherein the illumination optical system includes strip-shaped lighting disposed so as to surround a vehicle body in a width direction, and
• wherein the inspection target surfaces are coated surfaces in which a clear layer is formed on a base coat layer, and an optical characteristic of the inspection target surface model includes a scattering characteristic of the base coat layer and a reflection characteristic of the clear layer.

A non-transitory computer-readable recording medium storing a program for causing a computer to execute generating training image data for supervised machine learning for training a defect classifier to be applied to visual inspection, the program causing the computer to execute:

• arbitrarily selecting a defect model from defect models obtained by modeling shapes and optical characteristics of defects and stored on a defect model storage;
• arbitrarily selecting an inspection target surface model from inspection target surface models obtained by modeling shapes and optical characteristics of inspection target surfaces and stored on an inspection target surface model storage;
• arranging the selected defect model and the selected inspection target surface model in any space in which ray tracing is performed by ray tracing simulation software in which an illumination optical system, an image pickup optical system, and an imaging sensor including a plurality of pixels are modeled, tracing a plurality of light rays, calculating illuminance at each of the pixels based on an intensity and a number of light rays entering the pixels, and generating pseudo image data as the training image data based on the calculated illuminance, and
• generating the pseudo image data while at least one of an illumination optical system model or a model obtained by synthesizing the defect model and the inspection target surface model is moved by a minute amount and arranged at a plurality of different positions,
• wherein the illumination optical system includes strip-shaped lighting disposed so as to surround a vehicle body in a width direction, and
• wherein the inspection target surfaces are coated surfaces in which a clear layer is formed on a base coat layer, and an optical characteristic of the inspection target surface model includes a scattering characteristic of the base coat layer and a reflection characteristic of the clear layer.