Abstract
This paper presents a procedure for automatically fine-tuning the control parameters of a noise-tolerant matching algorithm. The construction of correspondence relations between 2D models and image representations will be executed by computing morphisms between relational structures. Tolerance parameters for model attributes can be modified in order to apply the matching algorithm to real world images. Evaluation functions are incorporated for measuring the quality of the correspondence relations.
An adaptation procedure automatically modifies the tolerance parameters to reach acceptable correspondence relations. For initializing the adaptation procedure the user only has to specify initial values of a minimum set of tolerance parameters. Geometrical dependencies between attributes of model components are employed for determining initial values for the rest of the tolerance parameters. Additionally, the user has to define several criteria for accepting correspondence relations. These acceptance criteria will be specified by fixing thresholds for the evaluated correspondence relations. Several modification strategies are included for reacting appropriately on the outcome of the evaluation functions.
The implemented system will be demonstrated in the practical application area of inspecting classes of Integrated Circuits to detect manufacturing errors.
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Literature
A. Fleming: Geometric relationships between toleranced features; Artificial Intelligence 37, pp. 403 — 412,1988.
B. Widrow, et al.: Neural nets for adaptive filtering and adaptive pattern rec.; IEEE Computer, pp. 25 — 39,1988.
K.N. Ngan, et al.: Geometric modelling of IC die bonds for inspection; Pattern Rec. Letters 10, pp. 47 — 52,1989.
J. Pauli, et al.: Wissensgesteuerter Strukturvergleich; Arbeitsbericht Ra 359/2–4, (in german), 1989.
B. Radig: Image sequence analysis using relational structures; Pattern Recognition 17, No. 1, pp. 161 — 167,1984.
A. Rosenfeld, A.C. Kak: Digital picture processing, 2nd ed. Vol. I and II; Academic Press, Orlando, 1982.
S. Ullman: Aligning pictorial descriptions: An approach to object recognition; Cognition 32, pp. 193 — 254,1989.
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© 1990 Springer-Verlag Berlin Heidelberg
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Pauli, J. (1990). Recognizing 2D Image Structures by Automatically Adjusting Matching Parameters. In: Marburger, H. (eds) GWAI-90 14th German Workshop on Artificial Intelligence. Informatik-Fachberichte, vol 251. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-76071-6_33
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DOI: https://doi.org/10.1007/978-3-642-76071-6_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-53132-6
Online ISBN: 978-3-642-76071-6
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