SOFTWARE DESIGN PATTERN FOR EQUIPMENT OF AUTOMATIC MASK INSPECTION SYSTEMS IN MICROELECTRONICS

Main Article Content

S. AVAKOV
A. VORONOV
V. GANCHENKO

Abstract

The paper investigates a relevant applied problem associated with software development for building equipment of automatic mask inspection systems and quality control topological structures in the microelectronics industry. This problem is one of key issues of design flow for equipment of automatic mask inspection systems and automatic defects detection. An original approach is proposed for selecting the sharpness function. Experiments have been conducted that confirm the effectiveness of original approach for obtaining high-quality initial images in equipment of automatic mask inspection systems using a technical vision system and, as a result, increases the percentage of yield of suitable products in microelectronics.

Article Details

How to Cite
AVAKOV, S., VORONOV, A., & GANCHENKO, V. (2024). SOFTWARE DESIGN PATTERN FOR EQUIPMENT OF AUTOMATIC MASK INSPECTION SYSTEMS IN MICROELECTRONICS. Vestnik of Polotsk State University. Part C. Fundamental Sciences, (2), 2-9. https://doi.org/10.52928/2070-1624-2024-43-2-2-9
Author Biographies

S. AVAKOV, Planar JSC, Minsk

д-р техн. наук, доц.

A. VORONOV, United Institute of Informatics Problems of NAS of Belarus, Minsk

канд. техн. наук, доц.

V. GANCHENKO, United Institute of Informatics Problems of NAS of Belarus, Minsk

канд. техн. наук

References

Avakov, S., Ovchinnikov, V., Karpovich, S., Titko, E., & Trapashko, G. (2007). Optiko-mehanicheskie kompleksy dlja bezdefektnogo izgotovlenija fotoshablonov 0,35 mkm i 90 nm. Fotonika, (6), 35–39. (In Russ.).

Falk, G. (2018). Gibkie reshenija dlja opticheskogo kontrolja kachestva. Nanoindustrija, (1), 24–26. DOI: 10.22184/1993-8578.2018.80.1.24.26. (In Russ.).

Buch, G. (1999). Ob"ektno-orientirovannyj analiz i proektirovanie s primerami prilozhenij na C++. St. Petersburg: Nevskij dialekt. (In Russ.).

Boggs, U., & Boggs, M. (2000). UML i Rational Rose. Moscow: Lori. (In Russ.).

Soifer, V. A. (2003). Metody komp'yuternoi obrabotki izobrazhenii. Moscow: Fizmatlit. (In Russ.).

Gonsales, R., & Vuds, R. (2005). Tsifrovaya obrabotka izobrazhenii. Moscow: Tekhnosfera. (In Russ.).

Dudkin, A. A., & Sadykhov, R. Kh. (2008). Obrabotka izobrazhenii v proektirovanii i proizvodstve integral'nykh skhem. Minsk: UIIP NAS Belarus. (In Russ.).

Ablameiko, S. V., Kharin, Yu. S., Sadykhov, R. Kh., Starovoitov, V. V., & Tuzikov, A. V. (2003). Raspoznavanie i analiz stokhasticheskikh dannykh i tsifrovykh izobrazhenii. Vestnik Fonda fundamental'nykh issledovanii, (4), 101–106. (In Russ.).

Krasnoproshin, V. V., & Obraztsov, V. A. (2006). Problems of Solvability and Choice of Algorithms for Decision Making by Precedence. Pattern Recognit. Image Anal., 16(2), 155–169. DOI: 10.1134/S1054661806020027.

Gamma, E., Khelm, R., Dzhonson, R., & Vlissides, Dzh. (2001). Priemy ob"ektno-orientirovannogo proektirovaniya. Patterny proektirovaniya. St. Petersburg: Piter. (In Russ.).

Larman, K. (2002). Primenenie UML i shablonov proektirovaniya. Moscow: Vil'yams. (In Russ.).

Knut, D. E. (2000). Iskusstvo programmirovaniya: v 4 t. T. 3: Sortirovka i poisk [The Art of Computer Programming (in 4 vol., Vol. 3: Sorting and Searching)]. – St. Petersburg: Vil'jams. (In Russ.).

Tian, Q., Fainman, I., & Lee, S. H. (1988). Comparison of statistical pattern-recognition algorithms for hybrid processing. II. Eigenvector-based algorithm. J. Optical Society America A, 5(10), 1669–1681. DOI: 10.1364/JOSAA.5.001670.

Moganti, M., Erçal, F., Dagli, C. H., & Tsunekawa, S. (1996). Automatic PCB Inspection Algorithms: A Survey. Comput. Vis. Image Underst., 63(2), 287–313. DOI: 10.1006/cviu.1996.0020.