Geometrical stereo matching image guidance for ground vehicle on focused image pixel grouping and stacked images statistical operation

Akira Akiyama; Nobuaki Kobayashi; Hideo Kumagai; Eiichiro Mutoh; Hiromitsu Ishii

doi:10.1117/12.929508

19 October 2012 Geometrical stereo matching image guidance for ground vehicle on focused image pixel grouping and stacked images statistical operation

Akira Akiyama, Nobuaki Kobayashi, Hideo Kumagai, Eiichiro Mutoh, Hiromitsu Ishii

Author Affiliations +

Proceedings Volume 8487, Novel Optical Systems Design and Optimization XV; 848709 (2012) https://doi.org/10.1117/12.929508
Event: SPIE Optical Engineering + Applications, 2012, San Diego, California, United States

Abstract

We have developed the geometrical stereo matching image guidance for ground vehicle on focused image pixel grouping and stacked images statistical operation. The two imagers are mounted on the 5 degrees of freedom gimbal unit. The gimbal unit gives each imager the independent yaw and pitch movement, and makes the same rigid yaw rotation on the two imagers. The fast focus image is derived from the calculating the developed wavelet focus measure value of the horizontal high pass image and the vertical high pass image of the Daubechies wavelet transformed image. The highest wavelet focus measure value among them gives the best focus image directly. This focusing operation works finely similar to the other differential image techniques. We used the stereo matching operation between the binary blocked high pass images corresponding to the best focus image. To construct the binary blocked high pass image, we apply the 8 directional adjacent pixel connection to the binary high pass image. The group of the main block elements of the binary image can work as the appropriate matching block. The wide image and narrow image stereo matching operation on the binary high pass image give the correct matching. In particular the narrow image stereo matching operation provides the common area of the right image and the left image. For finding the surface we used the brightness variation of each pixel point through the stacked images for the focusing operation. The kinds of the calculated brightness variations are the standard variation and the absolute deviation from the average brightness on each pixel point. We applied the threshold to the variation and deviation to classify the image area into the mild variation brightness surface area and rough variation brightness surface area. The rough variation brightness surface area covers the group of the main blocked elements in the binary image.

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Akira Akiyama, Nobuaki Kobayashi, Hideo Kumagai, Eiichiro Mutoh, and Hiromitsu Ishii "Geometrical stereo matching image guidance for ground vehicle on focused image pixel grouping and stacked images statistical operation", Proc. SPIE 8487, Novel Optical Systems Design and Optimization XV, 848709 (19 October 2012); https://doi.org/10.1117/12.929508

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KEYWORDS

Binary data

Imaging systems

Linear filtering

Cameras

Computer programming

Wavelets

Image processing

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