The objective of pattern matching problem is to find the most similar image pattern in a scene image by matching to an instance of the given pattern. For pattern matching, most distinctive features are computed from a pattern that is to be searched in the scene image. Scene image is logically divided into sliding windows of pattern size, and all the sliding windows are to be checked with the pattern for matching. Due to constant matching between the pattern and the sliding window, the matching process should be very efficient in terms of space, time and impacts due to orientation, illumination and occlusion must be minimized to obtain better matching accuracy. This paper presents a novel local feature descriptor called Multi-variant Local Binary Pattern (MVLBP) for pattern matching process while LBP is considered as base-line technique. The efficacy of the proposed pattern matching algorithm is tested on two databases and proved to be a computationally efficient one.