Method of and apparatus for classifying image

An apparatus for classifying an image, the apparatus extracting a feature vector from the image, wherein the feature vector comprises a plurality of first features, each of the first features corresponds to a combination of a plurality of first areas arranged in the direction of a first axis, a plurality of second areas arranged in the direction of a second axis intersecting with the direction of the first axis, and one of a plurality of predetermined orientations, and the apparatus comprises:

• a difference calculating unit which with respect to each of the first features, acquires a difference between sums or mean values of pixels of the plurality of first areas in the corresponding combination to obtain a first difference vector in the direction of the first axis, acquires a difference between sums or mean values of pixels of the plurality of second areas in the corresponding combination to obtain a second difference vector in the direction of the second axis, and acquires a first projection difference vector and a second projection difference vector projected by the first difference vector and the second difference vector on the line of the predetermined orientation in the corresponding combination;
• and
• a feature calculating unit which acquires the sum of magnitudes of the first projection difference vector and the second projection difference vector as the first feature;
• and
• a classifying unit which classifies the image according to the extracted feature vector.

A method of generating a classifier for discriminating object images from non-object images, comprising:

• extracting a feature vector from an input image, wherein the feature vector comprises a plurality of first candidate features, each of the first candidate features corresponds to a candidate combination of a plurality of first areas arranged in the direction of a first axis, a plurality of second areas arranged in the direction of a second axis intersecting with the direction of the first axis, and one of a plurality of predetermined orientations, and the extracting of each of the first candidate features comprises:
• acquiring a difference between sums or mean values of pixels of the plurality of first areas in the corresponding candidate combination to obtain a first difference vector in the direction of the first axis, and acquiring a difference between sums or mean values of pixels of the plurality of second areas in the corresponding candidate combination to obtain a second difference vector in the direction of the second axis;
• acquiring a first projection difference vector and a second projection difference vector projected by the first difference vector and the second difference vector on the line of the predetermined orientation in the corresponding candidate combination;
• and
• acquiring the sum of magnitudes of the first projection difference vector and the second projection difference vector as the first candidate feature;
• and
• training the classifier according to the extracted feature vectors.

An apparatus for generating a classifier for discriminating object images from non-object images, the apparatus extracting a feature vector from the input image, wherein the feature vector comprises a plurality of first candidate features, each of the first candidate features corresponds to a candidate combination of a plurality of first areas arranged in the direction of a first axis, a plurality of second areas arranged in the direction of a second axis intersecting with the direction of the first axis, and one of a plurality of predetermined orientations, and the apparatus comprising:

• a difference calculating unit which with respect to each of the first candidate features, acquires a difference between sums or mean values of pixels of the plurality of first areas in the corresponding candidate combination to obtain a first difference vector in the direction of the first axis, acquires a difference between sums or mean values of pixels of the plurality of second areas in the corresponding candidate combination to obtain a second difference vector in the direction of the second axis, and acquires a first projection difference vector and a second projection difference vector projected by the first difference vector and the second difference vector on the line of the predetermined orientation in the corresponding candidate combination;
• and
• a feature calculating unit which acquires the sum of magnitudes of the first projection difference vector and the second projection difference vector as the first candidate feature;
• and
• a training unit which trains the classifier according to the extracted feature vectors.