Intervention surgery strongly requires information on the guide-wire position under the monitoring of X-ray video. Hence, the related researches that can locate the guide-wire position such as guide-wire detecting or tracking have become popular. However, most of the existing methods require a lot of resources for computing or large data for training since in the Xray videos there are internal physicals such as anatomical skeleton contours and organs that are quite similar to a guide-wire. This work presents a practical method that only requires the moderate number of training data for detecting a guide-wire tip in an X-ray video sequence during the percutaneous coronary intervention surgery. The method applies maximally stable extremal regions (MSERs) combined with modified multi-filters (region area range filter and stroke width variation filter) for region detection and local binary patterns (LBPs) for guide-wire recognition. The motivation for applying MSER and LBP are the robust ability and the low requirement of resources. The approach evaluated on 20 different sequences of X-ray videos, total 1295 frames. Fifty selected frames were used as training templates and others to experiment. The method was successfully performed to the detecting guide-wires with p-value < 0.01 compared with conventional MSER methods, 93.7% average detection accuracy, and 21 fps average speed.