DocumentCode :
1515503
Title :
Predicting and estimating the accuracy of a subpixel registration algorithm
Author :
Cox, Ingemar J. ; Kruskal, Joseph B. ; Wallach, Deborah A.
Author_Institution :
AT&T Bell Lab., Murray Hill, NJ, USA
Volume :
12
Issue :
8
fYear :
1990
fDate :
8/1/1990 12:00:00 AM
Firstpage :
721
Lastpage :
734
Abstract :
It is shown that an efficient practical registration algorithm previously described by H.G. Barrow et al. (1977) can provide high-accuracy registration. Experiments with a quantized video image of a solid triangle yielded registration that was accurate to 3% of the interpixel spacing (i.e. accurate to 0.5 mils) in the x and y directions and 0.015° in rotation. It may also be important to predict the accuracy in advance, to see whether specifications can be met and to estimate accuracy during registration, in order to control quality. The authors provide practical formulas for both purposes for two kinds of image point data: edge detection (ED) data and direct measurement (DM) data. In two experiments using ED data, the predicted, estimated, and observed accuracies are all in agreement. The prediction theory developed suggests five precautions to avoid loss of registration accuracy. Perhaps most important is Precaution c, the necessity of the ED case not to have a large fraction of the total segment length of the model aligned with the horizontal or vertical directions of the pixel grid. When the model consists largely of horizontal and vertical segments, a good way to observe this precaution is to tilt the pixel grid a few degrees away from perfect alignment, e.g. by tilting the video camera. A third experiment verifies that violating Precaution c can seriously degrade accuracy
Keywords :
computer vision; estimation theory; iterative methods; accuracy; computer vision; direct measurement; edge detection; image point data; prediction theory; quantized video image; solid triangle; subpixel registration algorithm; Accuracy; Assembly; Connectors; Delta modulation; Image segmentation; Optical fibers; Prediction theory; Predictive models; Printed circuits; Solids;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.57665
Filename :
57665
Link To Document :
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