Performance analysis of locality preserving image hash

Bit extraction is an essential component of an image hashing system. A good bit extraction scheme should preserve the performance achieved at the feature representation level. In other words the robustness discrimination tradeoff measured by ROC analysis should be preserved. This is dependent on several factors such as, the encountered noise and the number of bits that can be extracted per sample. This paper investigates the relationship between these parameters and proposes some theoretical bounds in achieving a good tradeoff. The analysis primarily focuses on the bit extraction method proposed in [1] and its performance is compared with a scalar quantization based hashing method.