Authentication of face is a considerable challenge in pattern recognition since the face can undergo a large variety of changes in illumination, facial expression and aging. This paper proposes Diverse- Chromatic Texture Pattern (DCTP), a technique for effective feature extraction which aids face recognition through Content-Based Image Retrieval (CBIR). It extracts the spatio-chromatic information of an image by generating three sequences of patterns from inter-channel information of an image. This produces three different successions of diversified chromatic feature vectors which extract the unique information from each interactive plane (RGB, GBR and BRG) of an image. The information is extracted by forming different sequences of patterns according to the position of mid-pixel. The analysis made in CASIA database (DB1) shows significant improvement over the previous works like Local Binary Pattern (LBP) (91.75%/75.18%), Local Tetra Pattern (LTrP) (91.64%/76%) and Local Oppugnant Color Texture Pattern (LOCTP) (99.21%/89.38%) as 99.67%/93.47% in terms of Average Precision/ Average Recall. The analysis on Indian Face Database (DB2) shows the result of DCTP is improved from LBP (78.64%/57.35%), LTrP (79.84%/56.8%) and LOCTP (82.64%/58%) to 84.06%/ 58.7%.