Propose a novel deep neural network framework embedded with low-level features (LCNN) for salient object detection in complex images. Utilise the advantage of convolutional neural networks to automatically learn the high-level features that capture the structured information and semantic context in the image. Experiments on three challenging benchmarks demonstrate our algorithm to be effective and superior than most low-level oriented state-of-the-arts in terms of precision-recall curves, F-measure and mean absolute errors.