Analysis of Edge Detection in Bar Code Symbols: An Overview and Open Problems

Abstract

Accurate edge localization is essential in bar code decoding. Since speckle noise is the most dominant form of noise in laser bar code scanners, it is important to fully understand its effects on edge detection. Starting with the basic statistical properties of speckle patterns, we present stochastic analysis of speckle noise. We derive the autocorrelation function and power spectral density (PSD) of the noise in terms of intensity distribution of the scanning beam. We then study the signal-to-noise ratio for signals that result from scanning different configurations of edges. Next, we consider statistical properties of edge localization error caused by speckle noise. We show that the standard deviation of the error is determined by the PSD of the noise and relative positions of edges in a bar code symbol. Based on the analysis presented here, we propose new criteria for system design.