Факультет математики, фізики та інформаційних технологій

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https://dspace.onu.edu.ua/handle/123456789/37442

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Перегляд Факультет математики, фізики та інформаційних технологій за Автор "Zhang Aifei"

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    Application of image quality processing in face recognition
    (Одеський національний університет імені І. І. Мечникова, 2024) Zhang Aifei; Джан Айфей
    This paper focuses on the use of surface microstructure image analysis to enhance the reliability and accuracy of anti-counterfeiting technology, with the aim of improving the anti-counterfeiting level of commodities and combating counterfeiting products. At first, the introduction explains the importance of microstructure image analysis of object surface in anti-counterfeiting technology and its application nowadays, clarifies the purpose, significance, content, general idea, research method and the structure and framework of the paper, and also highlights the innovation of the research. After that, the thesis discusses the microstructure image acquisition technology in detail, covering the composition of the image acquisition system, the working principle, the selection of imaging technology, the setting of imaging parameters and the image acquisition process. Image pre-processing and enhancement are explored in depth, including the removal of image noise, contrast adjustment, image sharpening and image de-blurring and other technical means to improve image quality for subsequent processing. In the part of image feature extraction and matching, common feature extraction methods such as KAZE are introduced and their advantages and disadvantages are analyzed. The process of generating feature descriptors and the application scenarios of many common feature matching algorithms are described in detail, and the validity and reliability of the matching results are also discussed. In the anti-counterfeiting algorithm design and implementation section, an image feature-based anti-counterfeiting algorithm is designed and agreed upon to distinguish between genuine and fake items. A performance evaluation of the algorithm is implemented, an optimization strategy is proposed, and the specific flow and test results of the algorithm implementation are shown. In the experiments and case studies section, the composition and configuration of the experimental platform are introduced, the experimental design process is described in detail, the experimental results are analyzed, the effectiveness and reliability of the algorithm are verified, and the effectiveness of the algorithm in the anti-counterfeiting field is analyzed in combination with practical application cases. In the summary and outlook section, the main findings and results of the study are summarized, the problems and shortcomings encountered in the research process are pointed out, and the future research directions and development trends are envisioned, with specific proposals and initiatives for further improvement of the study given.