Multiresolution Object-of-Interest Detection for Images with Low Depth of Field

This paper describes a novel multiresolution image segmentation algorithm for separating sharply focused objects-of-interest from other foreground or background objects in low depth of eld DOF images, such as sports, telephoto, macro, and microscopic images. The algorithm takes a multiscale context-dependent approach to segment images based on features extracted from wavelet coe cients in high frequency bands. The algorithm is fully automatic in that all parameters are image independent. Experiments with the algorithm on more than 100 low DOF images have shown results close to the human segmentation of these images. Besides high accuracy, the algorithm also provides high speed. A 768512 pixel image can be segmented within two seconds on a Pentium Pro 300MHz PC.

• Type: Conference
• Year: 1999
• Where: ICIAP
• Authors: Jia Li, James Ze Wang, Robert M. Gray, Gio Wiederhold
• Keywords: Algorithm, Eld DOF Images, ICIAP 1999, Image Processing, Image Segmentation Algorithm