Center Symmetric-Local Binary Pattern (CSLBP) is textured based operator which is mostly used as keypoint descriptor, it is 256-length descriptor to represent single keypoint or affine patch. This operator is an extension of Local Binary Pattern (LBP) operator. The CSLBP descriptor is computationally simple, effective, and robust for various image transformations such as illumination change and image blurring. However, the space and time utilization of CSLBP can be improved by simple compression which can make CSLBP a smart selection for large databases and smart phones. In this paper, we propose simple compression of CSLBP without loss of its discriminative power. We reduce the descriptor length (dimensions) upto 50% without applying any dimensionality reduction techniques such as PCA or LDA. We evaluate our framework on state-of-the-art matching protocols and compare the effectiveness of proposed compressed descriptor (Q-CSLBP) with CSLBP, SIFT and PCA-SIFT.