Motivated by DNA copy number variation analysis based on next generation sequencing data, we consider the problem of identifying sparse short segments hidden in an ultra long linear sequence of data with unspecified noise distribution.Based on a local median transformation, we propose a computationally efficient method called robust segment identifier (RSI), which provides a robust and near-optimal solution for segment identification over a wide range of noise distributions.