Portable artificial electronic nose (E-nose) system suffers from noisy fluctuation in surroundings such as temperature, vapor concentration, and gas flow, because its measuring condition is not controled precisely as in the laboratory. It is important to develop a simple and robust vapor recognition technique applicable to this uncontrolled measurement, especially for the portable measuring and diagnostic system which are expanding its area with the improvements in micro bio sensor technology. This study used a PDA-based portable E-nose to collect the uncontrolled vapor measurement signals, and applied the image matching algorithm developed in the previous study on the measured signal to verify its robustness and improved accuracy in portable vapor recognition. The results showed not only its consistent performance under noisy fluctuation in the portable measurement signal, but also an advanced recognition accuracy for 2 similar vapor species which have been hard to discriminate with the conventional maximum sensitivity feature extraction method. The proposed method can be easily applied to the data processing of the ubiquitous sensor network (USN) which are usually exposed to various operating conditions. Furthermore, it will greatly help to realize portable medical diagnostic and environment monitoring system with its robust performance and high accuracy.