An image processing system comprising: an input interface configured to receive a first direction image corresponding to a top view of a semiconductor device in a first direction, and a second direction image corresponding to a side view of the semiconductor device in a second direction which intersects the first direction at a first height at which the first direction image is generated; a processor configured to: perform an edge detection operation for detecting an edge of a feature of the semiconductor device based on the first direction image; perform an image binarization operation on the first direction image to determine pixels having a brightness greater than a threshold brightness to be an inner region, based on brightness information about pixels of the first direction image; calculate an edge detection ratio value by dividing the number of edges included in the inner region by a total number of edges detected in the first direction image; and a learning device configured to: compare a first line width obtained based on the inner region of the image binarization operation, and a second line width obtained based on the second direction image through machine learning; and learn the edge detection ratio value of the image binarization operation which maximizes a correlation between the first line width and the second line width by adjusting the threshold brightness. an input interface configured to receive a first direction image corresponding to a top view of a semiconductor device in a first direction, and a second direction image corresponding to a side view of the semiconductor device in a second direction which intersects the first direction at a first height at which the first direction image is generated; a processor configured to: perform an edge detection operation for detecting an edge of a feature of the semiconductor device based on the first direction image; perform an image binarization operation on the first direction image to determine pixels having a brightness greater than a threshold brightness to be an inner region, based on brightness information about pixels of the first direction image; calculate an edge detection ratio value by dividing the number of edges included in the inner region by a total number of edges detected in the first direction image; and a learning device configured to: compare a first line width obtained based on the inner region of the image binarization operation, and a second line width obtained based on the second direction image through machine learning; and learn the edge detection ratio value of the image binarization operation which perform an edge detection operation for detecting an edge of a feature of the semiconductor device based on the first direction image; perform an image binarization operation on the first direction image to determine pixels having a brightness greater than a threshold brightness to be an inner region, based on brightness information about pixels of the first direction image; calculate an edge detection ratio value by dividing the number of edges included in the inner region by a total number of edges detected in the first direction image; and a learning device configured to: compare a first line width obtained based on the inner region of the image binarization operation, and a second line width obtained based on the second direction image through machine learning; and learn the edge detection ratio value of the image binarization operation which compare a first line width obtained based on the inner region of the image binarization operation, and a second line width obtained based on the second direction image through machine learning; and learn the edge detection ratio value of the image binarization operation which maximizes a correlation between the first line width and the second line width by adjusting the threshold brightness.