Decoding Visual Brand Identity Through Computer Vision

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Authors: M D Rokon Islam Emon, Tahsina Khan
Cited by: 1
References: 60

Abstract

This chapter explores the transformative role of computer vision in decoding and analyzing visual brand identity within today's visually driven marketplace. It highlights how AI-powered techniques such as logo detection, color palette extraction recognition enable marketers to objectively measure and manage the core visual elements that shape brand perception. By integrating machine learning and image processing, brands can achieve greater consistency, track competitive positioning, and better understand consumer responses across digital platforms. The chapter also addresses key challenges including data variability, cultural nuances, and ethical considerations, while exploring future directions like multimodal AI and real-time brand monitoring. Through a blend of theoretical insights and practical case studies, this work offers a comprehensive perspective on how AI-driven visual analysis is redefining branding strategies, providing valuable implications for academics and marketing professionals aiming to leverage emerging technologies to strengthen brand identity and engagement.

Fields of Study & Subjects

Consumer Behavior in Brand Consumption and Identification Corporate Identity and Reputation Digital Media and Visual Art

Publication details

Journal / source
Advances in computational intelligence and robotics book series
Publisher
IGI Global Scientific Publishing
Pages
33–66
Publication date
20 February 2026
Document type
Book chapter