In this paper, a fingerprint pre-process and identification algorithm is implemented using the TMS320C6713 DSP starter kit (DSK) module, along with the Authentec AFS 8600 fingerprint sensor. Database: Acquisition is performed using a solid state sensor. The sensor postulates emerge from the theory of the Electric Field technology. Method: Images are first subjected to a frequency and orientation processing. This is achieved using Gabor-based filters. This processing has been optimized and implemented on the DSP system. A new method has been developed in order to extract the feature vector of the fingerprint image. A grid, centered at the corepoint of the image, is applied to the fingerprint image in order to derive local information. Classification algorithms are developed, which include training as well as evaluating phase. The types of classifiers used were based on the Bayesian approach along with the K-nearest neighbour. Results: An identification accuracy of 90% was achieved which is comparable to other procedures described in the literature. Conclusion: The combination of a fingerprint processing and identification algorithm using a low cost sensor and DSP module has been presented.