Surface defect inspection method and surface defect inspection apparatus

A surface defect inspection method comprising:

• an image input step of acquiring an original image by capturing an image of a subject of an inspection;
• a texture feature image generating step of generating texture feature images by applying a filtering process using spatial filters to the original image;
• a texture feature extracting step of generating a feature vector at each position of the original image, by extracting a value at a corresponding position from each of the texture feature images, for each of the positions of the original image;
• an abnormality level calculating step of generating an abnormality level image representing an abnormality level for each position of the original image, by calculating, for each of the feature vectors, an abnormality level in a multi-dimensional distribution formed by the feature vectors;
• and
• a detecting step of detecting a part having the abnormality level that is higher than a predetermined level in the abnormality level image as a defect portion or a defect candidate portion.

A surface defect inspection apparatus comprising:

• an image capturing unit configured to capture a subject of an inspection;
• an image input unit configured to acquire an original image of the subject of the inspection, the original image being captured by the image capturing unit;
• a texture feature image generating unit configured to generate texture feature images by applying a filtering process using spatial filters to the original image;
• a texture feature extracting unit configured to generate a feature vector at each position of the original image by extracting a value at a corresponding position from each of the texture feature images, for each of the positions of the original image;
• an abnormality level calculating unit configured to generate an abnormality level image representing an abnormality level for each position of the original image, by calculating, for each of the feature vectors, an abnormality level in a multi-dimensional distribution formed by the feature vectors;
• and
• a detecting unit configured to detect a part having the abnormality level that is higher than a predetermined level in the abnormality level image as a defect portion or a defect candidate portion.