Image retrieval systems rely heavily on computing similarity between high-dimensional feature vectors, an operation that grows computationally expensive as databases scale. Recent advances in quantum computing offer promising alternatives through quantum inner product algorithms. This chapter presents a comprehensive experimental comparison of two approaches: the Swap Test-based Quantum Inner Product (ST-QIP) and the Amplitude Estimation-based Quantum Inner Product (AE-QIP). Through systematic e