In this paper, the authors introduced the theory about LMCCD (line-matrix CCD) mapping camera firstly. On top of the
introduction were consists of the imaging system of LMCCD mapping camera. Secondly, some pivotal designs which
were Introduced about the imaging system, such as the design of focal plane module, the video signal's procession, the
controller's design of the imaging system, synchronous photography about forward and nadir and backward camera and
the nadir camera of line-matrix CCD. At last, the test results of LMCCD mapping camera imaging system were
introduced. The results as following: the precision of synchronous photography about forward and nadir and backward
camera is better than 4 ns and the nadir camera of line-matrix CCD is better than 4 ns too; the photography interval of
line-matrix CCD of the nadir camera can satisfy the butter requirements of LMCCD focal plane module; the SNR tested
in laboratory is better than 95 under typical working condition(the solar incidence degree is 30, the reflectivity of the
earth's surface is 0.3) of each CCD image; the temperature of the focal plane module is controlled under 30° in a
working period of 15 minutes. All of these results can satisfy the requirements about the synchronous photography, the
temperature control of focal plane module and SNR, Which give the guarantee of precision for satellite photogrammetry.
Multilinear CCD Sensor was often used on space cameras to obtain multispectral images with each line representing
different band channels. However images of different band channels obtained at the same time didn't coincide as there
were spaces between lines. Pixel numbers to be adjusted between images of different channels varied when the space
camera worked by swaying forward and backward or adjusted row transfer period to compensate image movement. An
automatic multispectral images synthesis algorithm of space camera was put forward on the basis of analysis of such
phenomenon. In this algorithm a new evaluation function was used to determine pixel numbers to be adjusted and the
image regions of each band channel to be clipped. In this way images of different band channels could be synthesized
automatically to obtain an accurate colorful image. This algorithm can be used to dispose a large mount of images from
space camera directly without any manual disposal so that efficiency could be improved remarkably. In validation
experiments the automatic multispectral images synthesis algorithm was applied in synthesis of images obtained from
outside scene experiment of a multispectral space camera. Result of validation experiments proved that the automatic
multispectral images synthesis algorithm can realize accurate multispectral images synthesis of space camera and the
efficiency can be improved markedly.
This paper (SPIE Paper 60310G) was removed from the SPIE Digital Library on 8 August 2008 upon learning that portions of the paper are identical or similar to material contained in a Master's Thesis by Taeyoung Choi at South Dakota State University in 2002 titled "IKONOS Satellite on Orbit Modulation Transfer Function (MTF) Measurement using Edge and Pulse Method," without attribution or credit to the source.
As stated in the SPIE Publication Ethics Guidelines, "SPIE defines plagiarism as the reuse of someone else's prior ideas, processes, results, or words without explicit attribution of the original author and source, or falsely representing someone else's work as one's own. Unauthorized use of another researcher's unpublished data or findings without permission is considered to be a form of plagiarism even if the source is attributed. SPIE considers plagiarism in any form, at any level, to be unacceptable and a serious breach of professional conduct."
It is SPIE policy to remove such papers and to provide citations to original sources so that interested readers can obtain the information directly from these sources.
In this paper, the authors put forward a new method for print number recognition when we research on the OCR (Optical Character Recognition). It's different from the traditional method such as NN (Neural Networks) recognition or model matching. By this method, the number waiting for recognizing was treated as the fingerprint lines, then, defined and extracted the features about the number for recognition. At end of the paper, an experiment result is given.
KEYWORDS: Cameras, Digital signal processing, Control systems, Image processing, Signal processing, Video processing, CMOS sensors, Video, Computing systems, Binary data
A smart camera is composed of a video sensing, high-level video processing, communication and other affiliations within a single device. Such cameras are very important devices in quality control systems. This paper presents a prototyping development of a smart camera for quality control. The smart camera is divided to four parts: a CMOS sensor, a digital signal processor (DSP), a CPLD and a display device. In order to improving the processing speed, low-level and high-level video processing algorithms are discussed to the embedded DSP-based platforms. The algorithms can quickly and automatic detect productions' quality defaults. All algorithms are tested under a Matlab-based prototyping implementation and migrated to the smart camera. The smart camera prototype automatic processes the video data and streams the results of the video data to the display devices and control devices. Control signals are send to produce-line to adjust the producing state within the required real-time constrains.
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