Abstract: Disclosed is a defect inspection device for determining anomaly of an inspection object. The defect inspection device may include: a lighting system which includes a light source for transmitting light onto the inspection object; and a dynamic diffuser located between the light source and the inspection object and capable of controlling a diffusivity of light transmitted onto the inspection object; and one or more processors for controlling the dynamic diffuser based on characteristics of the inspection object.

Abstract: Disclosed is a defect inspection device. The defect inspection device may include a lighting system designed for transmitting a lighting pattern having different illuminances for each area on a surface of an inspection object; a photographing unit for obtaining an image data of the inspection object; one or more processors for processing the image data; and a memory for storing a deep learning-based model. In addition, the one or more processors are adapted to control, the lighting system to transmit a lighting pattern having a different illuminance for each area on a surface of an inspection object, input, an image data obtained by the photographing unit into the deep learning-based model, wherein the image data includes a rapid change of illuminance in at least a part of the object surface; and determine, a defect on a surface of the inspection object using the deep learning-based model.

Abstract: Disclosed is a defect inspection device for determining anomaly of an inspection object. The defect inspection device may include: a lighting system which includes a light source for transmitting light onto the inspection object; and a dynamic diffuser located between the light source and the inspection object and capable of controlling a diffusivity of light transmitted onto the inspection object; and one or more processors for controlling the dynamic diffuser based on characteristics of the inspection object.