Fragile Bits in Palmprint Recognition

Recent years have witnessed a growing interest in developing automatic palmprint recognition methods. Among them, coding-based ones, representing the texture of a palmprint using a binary code, are most prevalent and successful. We find that not all bits in a code map generated by a specific coding scheme are equally consistent. A bit is deemed fragile if its value changes across code maps created from different images of the same palmprint. In this paper, we first analyze the fragile bits phenomenon in a state-of-the-art palmprint coding scheme, namely, binary orientation co-occurrence vector (BOCV). Then, based on our analysis, we extend BOCV to E-BOCV by incorporating fragile bits information in appropriate ways. Experiments conducted on the benchmark dataset demonstrate that E-BOCV can achieve the highest verification accuracy among all the state-of-the-art palmprint verification methods evaluated. To our knowledge, this is the first work investigating the fragile bits of coding-based palmprint recognition approaches.