• PRERANA PRATAP RANDHAVE
• YASH PRABHAKAR PATIL
• RITESH MADHAV PATE
• ABHISHEK PRAKASH PATIL
• Mr.SHRIKANT SHINDE

This project is designed to detect fake logos by comparing them with genuine ones. The detection process involves dividing the logo image into segments based on rows, columns, height, and width, so that each section can be analysed individually. Counterfeit logos have led to significant brand losses over time, not only financially but also by harming the reputation of the original products. These fake logos are often associated with low-quality items that misrepresent the brand’s image and reduce consumer trust. A logo serves as a distinct symbol that links a product to its rightful owner, and its use is legally protected through registration and approval. Manually inspecting these logos can be time-consuming and error-prone. Automating this process improves both accuracy and efficiency. Logo recognition has been widely studied due to its practical use in areas such as marketing, product verification, advertisement filtering, and digital media organization.

Keywords: Image Processing, Deep Learning, Convolutional Neural Networks, E-commerce.

"FAKE LOGO DETECTION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 4, page no.n19-n25, April-2025, Available :http://www.jetir.org/papers/JETIR2504D04.pdf

"FAKE LOGO DETECTION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 4, page no. ppn19-n25, April-2025, Available at : http://www.jetir.org/papers/JETIR2504D04.pdf