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AI Test Modeling for Computer Vision System—A Case Study

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Publicado en:Computers vol. 14, no. 9 (2025), p. 396-418
Autor principal: Gao, Jerry
Otros Autores: Agarwal Radhika
Publicado:
MDPI AG
Materias:
Software
Computer vision
Artificial intelligence
Automation
Modelling
Vision systems
Autonomous vehicles
Acceso en línea:Citation/Abstract
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Resumen:This paper presents an intelligent AI test modeling framework for computer vision systems, focused on image-based systems. A three-dimensional (3D) model using decision tables enables model-based function testing, automated test data generation, and comprehensive coverage analysis. A case study using the Seek by iNaturalist application demonstrates the framework’s applicability to real-world CV tasks. It effectively identifies species and non-species under varying image conditions such as distance, blur, brightness, and grayscale. This study contributes a structured methodology that advances our academic understanding of model-based CV testing while offering practical tools for improving the robustness and reliability of AI-driven vision applications.
ISSN:2073-431X
DOI:10.3390/computers14090396
Fuente:Advanced Technologies & Aerospace Database