A high-speed context-free marker controlled and minima imposition-free watershed transform is proposed for efficient multi-object detection and segmentation from a complex background. The context-free markers are extracted from a complex backgrounded multi-object image using a noise tolerant attention operator. These make high speed marker-controlled watershed possible without over-segmentation and region merging. The proposed method presents a marker-constrained labeling that can speed up the segmentation of the marker-controlled watershed transform by eliminating the necessity of the minima imposition. Simulation results show that the proposed method can efficiently detect and segment multiple objects from a complex background while reducing the over-segmentation and computation time.