In this paper, we present an end-to-end model, namely Seg-Edge bilateral constraint network. The iris edge map generated from rich convolutional layers optimize the iris segmentation by aligning it with the iris boundary. The iris region produced by the coarse segmentation limits the scope. It makes the edge filtering pay more attention to the interesting target. We compress the model while keeping the performance levels almost intact and even better by using l1-norm. The proposed model advances the state-of-the-art iris segmentation accuracies.