2026-09-26T21:36:43Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/94382026-06-05T20:26:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131024
Charles G. Sodini.
Fife, Keith G. (Keith Glen), 1974-
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-08-22T18:22:19Z
2005-08-22T18:22:19Z
1999
1999
http://hdl.handle.net/1721.1/9438
43412215
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.
Includes bibliographical references (p. 67-69).
This thesis describes the development of an automatic brightness adaptive imaging system for use in stereo vision algorithms implemented for a variety of processing architectures. A 256 x 256 array of wide dynamic range pixels with on-chip A/D converters provides the digital data path for a feedback network which controls the charge integration parameters at each pixel. The first goal of the project was to build a real-time demonstration of the imager with configurable compression functions. Secondly, electronic irising was employed by controlling the global charge integration time based on the average intensity of the image. In addition to electronic-irising, the imaging system employs a linear or a logarithmic compression scheme based on the image data. The controller fits the compression function to the image by comparing the average intensities of many different regions within the image. Finally, a 3-camera stereo-vision system was developed with data transfer to a PC through the PCI bus at 60fps. The imagers are synchronized and controlled based on the center imager's data which allows for consistent object correlation in stereo vision algorithms.
by Keith G. Fife.
S.B.
M.Eng.
141 p.
8257189 bytes
8256946 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science
A stereo vision system with automatic brightness adaptation
Thesis
application/pdf
false
Publication
unknown
unknown
<Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="099883d9-f8e6-4709-b1de-59a36a40a1db">
<Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type>
<Language>eng</Language>
<Title>A stereo vision system with automatic brightness adaptation</Title>
<PublishedIn>
<Publication>
</Publication>
</PublishedIn>
<PublicationDate>1999</PublicationDate>
<Authors>
<Author>
<DisplayName>Fife, Keith G. (Keith Glen), 1974-</DisplayName>
<Affiliation>
<OrgUnit>
</OrgUnit>
</Affiliation>
</Author>
</Authors>
<Editors>
</Editors>
<Publishers>
<Publisher>
<DisplayName>Massachusetts Institute of Technology</DisplayName>
<OrgUnit />
</Publisher>
</Publishers>
<License>http://dspace.mit.edu/handle/1721.1/7582</License>
<Keyword>Electrical Engineering and Computer Science</Keyword>
<Abstract>This thesis describes the development of an automatic brightness adaptive imaging system for use in stereo vision algorithms implemented for a variety of processing architectures. A 256 x 256 array of wide dynamic range pixels with on-chip A/D converters provides the digital data path for a feedback network which controls the charge integration parameters at each pixel. The first goal of the project was to build a real-time demonstration of the imager with configurable compression functions. Secondly, electronic irising was employed by controlling the global charge integration time based on the average intensity of the image. In addition to electronic-irising, the imaging system employs a linear or a logarithmic compression scheme based on the image data. The controller fits the compression function to the image by comparing the average intensities of many different regions within the image. Finally, a 3-camera stereo-vision system was developed with data transfer to a PC through the PCI bus at 60fps. The imagers are synchronized and controlled based on the center imager's data which allows for consistent object correlation in stereo vision algorithms.</Abstract>
<Access xmlns="http://purl.org/coar/access_right"
>
</Access>
</Publication>