Dieless bellows forming using local heating technique is an advanced flexible forming technology to produce bellows from straight tube without the use of dies. The deformation is induced by applying continuous compression, and local heating. Advantages of these processes are the absence of dies, applicability for various materials, suitability for flexible forming process including low batch production, flexibility on workpiece sizes and output geometries. However, the implementation of these processes is still low owing to the low quality, reproducibility, and production speed. The limitation of these dieless forming processes using local heating is caused by the absence of dies required to form the desired profile. Therefore deformation depends on temperature, length of heating zone, processing speed, speed ratio of feeding to fabrication speeds. In order to enhance the product quality in these dieless forming with local heating, real-time monitoring are necessary to identify deformation progress. Machine vision based on image processing technique was selected to monitor deformation behavior on dieless bellows forming process. The present paper describes real-time monitoring using image processing approach to monitor dimensional profile and temperature distribution during the process. The results show that machine vision is effective and efficient to monitor dynamic deformation of dieless bellows forming proces and able to identify abnormal process condition.