Multimodal biometric systems roughly used to achieve extreme recognition accuracy. This paper reports a novel multimodal biometric system employing intelligent technique to authenticate human by fusion of dorsal hand, palm and finger veins pattern. We improved an image analysis technique to separate region of interest (ROI) from dorsal hand, palm and finger veins image. After separating ROI we construct a sequence of preprocessing steps to enhance dorsal hand, palm and finger veins images using Median filter, Wiener filter, Contrast Limited Adaptive Histogram Equalization (CLAHE) and Homomorphic filter to improve vein image. Our intelligent technique is based on the following intelligent algorithms, namely; principal component analysis (PCA) algorithm for feature extraction and k-Nearest Neighbors (K-NN) classifier for matching operation. The database selected was Bosphorus Hand Vein Database, CASIA Multi-Spectral Palmprint Image Database V1.0 (CASIA database) and the Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT). The accomplished result for the fusion of three biometric traits was Correct Recognition Rate (CRR) is 99.21% with False Reject Rate (FRR) 0.04%.