Shape matching and retrieval is a challenging issue in computer vision owing to the complications in realizing highly accurate descriptors. Herein, a novel shape characterization, representation scheme is presented by blending phase congruency (PC) with histogram of oriented gradients (HOG), labelled as PC-HOG. Firstly, PC is applied on the shapes to obtain contour points that is then operated by HOG to formulate the feature vector. The resulting descriptor is evaluated on shape datasets like MPEG-7 CE shape-1 part B, TARI-1000 and Kimia’s 99. Relatively consistent Bull’s Eye Retrieval rate of 90% was achieved by the proposed descriptor across the diverse datasets. Also, noise analysis of the proposed descriptor in diverse datasets is performed to signify the scheme’s robustness against noise. Furthermore, the inherent nature of PC-HOG makes it to be invariant to different affine transformations. © 2019, Springer-Verlag London Ltd., part of Springer Nature.