Combining Multiple Image Features to Guide Automatic Portrait Cropping for Rendering Different Aspect Ratios

Nowadays there exists a large variety of aspect ratios used for both image rendering (e.g. print media, TV, cinema screens etc.) and image acquisition devices (e.g. still and video cameras, scanners etc.). In order to maintain the image’s original aspect ratio when adjusting for a different media, some level of cropping may be required, but the automatic zoom and crop method may not produce satisfactory results regarding image contents. This paper proposes an automatic method that analyses images and estimates the relevant content areas, avoiding distortions and main subject chopping. The analysis is performed by four feature extractors, each producing a grayscale image which indicates relevant image areas. The outputs of these extractors are then combined by means of a Genetic Algorithm (GA) optimization. Experiments involving a subjective evaluation of a set of automatically cropped images have shown that 77% of the 35 human observers considered images adjusted by the proposed approach better than or similar to the outputs of the automatic zoom and crop method.