Due to the tremendous increase in the digital image data, the efficient and effective image content-based search scheme for retrieving desired images from a large image repository is highly required. The biggest challenge in image retrieval scheme is to retrieve the desired multimedia images from the digital image repository with minimum time. Extracting significant image features with low dimensional feature descriptor play a significant role in improving retrieval outcomes. In the presented paper, an image retrieval scheme is proposed using fused low dimensional feature descriptor which is obtained by fusion of probability histogram-based HSV color moments and multiresolution based shape moments. The color moments and shape moments are extracted from the Laplacian filter based preprocessed image. The suggested scheme is implemented on a standard Corel-1K image dataset and the retrieval accuracy is measured using precision, recall, and F-score metrics. The experimental outcomes are also validated and compared with some existing state of the art image retrieval schemes and it outperforms over the existing ones.