¡@¡@Morphological image processing technique has been well applied to many image processing areas. However, its long computation time usually can¡¦t be accepted when run on a general purpose sequential computer. Instead of conventional image data representation, some special data structures have led to the development of efficient algorithms. ¡@¡@The quadtree data structure has been well applied to the field of computer vision such as image segmentation and compression. The quadtree with its hierarchical data structure are advantageous due to its ability to focus on the interesting subsets of the data. Thus, the quadtree data structure are particularly convenient for set operations. Therefore, the computation for morphology processing will be facilitated by using the quadtree data structure since the set operations are the basics of the morphology processing. ¡@¡@Although many fast morphological image processing methods have been presented, there is still a need for developing a distributed computing architecture for morphological processing. We propose a scheme direct connection for client to client to improve the data transfer efficiency. Also, the image data is compressed by the quadtree for the transmission efficiency. Due to the efficiency of the network connection and data compression, we have established an efficient web-based distributed work station for morphological image processing.