Food inspection apparatus, method of inspecting food, and method of learning in identification unit of food inspection apparatus

A food inspection apparatus comprising:

• a conveyor configured to convey a food as an inspection object to be confirmed that no foreign substance is mixed;
• a light source configured to irradiate the inspection object with light;
• an imager configured to capture an image of the inspection object;
• a wavelength emphasizer including at least one of a first optical filter attached to the light source or the imager, a second optical filter attached to an auxiliary light source, and a wavelength-specific light source, and configured to emphasize a characteristic wavelength reflected by at least one of the food and the foreign substance;
• and
• a processor configured to identify at least one of the food and the foreign substance,
• wherein the wavelength emphasizer emphasizes at least one of a foreign substance specific wavelength characteristic of the foreign substance and a good item specific wavelength characteristic of a good item of the food from light having a wavelength in a range of 300 nm to 1100 nm,
• wherein the processor is further configured to:
• normalize the image captured by the imager with 256 or less of gradations of light intensity to obtain lightened data;
• and
• be provided in advance with deep-learning to identify the foreign substance specific wavelength from the lightened data through a convolutional neural network for color reconstruction based on luminance by using the lightened data of plural image sheets, and
• wherein the processor identifies the foreign substance or the good item in line from the lightened data obtained through capturing the image during conveyance of the food by the conveyor.