5 July 1995 Locating multiple targets in complex images
Author Affiliations +
A new algorithm called the flying window locator algorithm (FWLA) is presented for locating multiple targets in complex images, in which the illumination is not uniform, the sizes of targets are small, and the colors of targets and their background are similar. The FWLA divides a complex image into subimages, called windows. To guarantee that a target of interest is completely in one of the windows, neighboring windows are overlapped so that each overlapped area is bigger than that of a target. Since a window defined in the FWLA is small, a scene component in a window is considered as having a similar shading or color. Hence, a window is composed of a mixture of component distributions, stemming from the different background and target regions in the window. A gradient clustering algorithm (GCA) is developed to separate a mixture in each window and segment a window. After segmentation, a `hole' concept is used to find the targets of interest based upon a priori knowledge of the target size, shape, and color. The FWLA is a non-iterative clustering algorithm and uses only fixed- point numbers to analyze an image. Consequently, it is fast and computationally efficient. Results of applying the FWLA to two different computer vision problems are presented.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhonghao Bao, Zhonghao Bao, Gerald M. Flachs, Gerald M. Flachs, Jay B. Jordan, Jay B. Jordan, } "Locating multiple targets in complex images", Proc. SPIE 2484, Signal Processing, Sensor Fusion, and Target Recognition IV, (5 July 1995); doi: 10.1117/12.213038; https://doi.org/10.1117/12.213038


Connection Machine Vision Applications
Proceedings of SPIE (June 05 1987)
Vision for automated imagery exploitation
Proceedings of SPIE (January 31 1991)
Automatic Target Detection On The Connection Machine
Proceedings of SPIE (February 18 1988)
Target segmentation algorithm based on feature field
Proceedings of SPIE (August 18 1998)

Back to Top