"保护品牌商誉：基于内容的图像检索CBIR技术研究"。

"Content-Based Image Retrieval (CBIR) for Brand Logos" is a Master's thesis that investigates the automatic detection of logos in general images. Brand logos are seen as valuable assets that represent a company's reputation, making it important for businesses to protect their brand identity. The complexity of automatically detecting logos in images is further heightened by intentional obfuscation techniques, such as color shifts or subtle image modifications, which make logos easily recognizable by humans but challenging for automated systems to identify. The thesis focuses on utilizing basic CBIR techniques to determine the presence of brand logos in larger images. CBIR systems retrieve images based on their similarity to a given query image, enabling users to search for images containing specific elements, such as dogs or brand logos. The study aims to address the challenges of logo detection in images and explore the potential applications of CBIR in brand protection and recognition. The research conducted in the thesis highlights the importance of automated logo detection for companies looking to safeguard their brand integrity in the digital sphere. By leveraging CBIR technology, businesses can efficiently identify and monitor the use of their logos across various platforms and media channels. The thesis contributes to the field of computer science by proposing practical solutions for improving logo detection accuracy and efficiency through content-based image retrieval methods. Overall, "Content-Based Image Retrieval (CBIR) for Brand Logos" offers valuable insights into the complexities of logo detection in images and the potential benefits of utilizing CBIR technology for brand protection. The thesis underscores the significance of automated logo detection in maintaining brand reputation and integrity in an increasingly digitalized world, providing a foundation for further research and development in the field of image recognition and analysis."