The curvature scale space (CSS) technique is one of the key techniques of the MPEG-7 international standard in Computer Vision and Image Processing. It was selected as a contour shape descriptor for MPEG-7 after substantial and comprehensive testing. However, to compute a CSS image in general needs to wait a long time. This is very disadvantageous when the CSS technique is applied to an object recognition system to perform real-time recognition. In order to solve this bottleneck problem, a hybrid method for fast computing the CSS image is proposed in the present paper. In the method, firstly the curve is evolved in low scale space, and after image noise is suppressed then the curvature is evolved directly. Numerical experiments show that the hybrid method can perform equally well as the existing method. It is suitable for recognizing a noisy curve of arbitrary shape at any scale or orientation. On the other hand, the hybrid method only requires 1/3~1/5 CPU time of the existing one. As a result, the CSS technique is improved significantly for real-time recognition.