Doorknob Hand Recognition System Design And Development

Among all of existing systems and methods of biometric identification basedon the human hands, most of them are needed to put the hands on the specialequipment to capture images for identification. These systems are difficult tocombine with the handle equipment, which means that it cannot recognize thenatural state of the hands. The terminal equipment of the feature recognitionsystem that this article describes simulate the shape of the doorknob. The user canachieving recognition while grasping the doorknob. This system has the followingadvantages: saving time, reducing the possibility of fraud, and enhance systemsecurity. The system collects faster, and the ways it collecting is more comfortable.The system includes the following four parts: design and implementation ofthe doorknob identification system equipment, image acquisition andpre-processing, region of interest(ROI) extraction, feature extraction andrecognition. The main contents include:(1) Design and implementation of the doorknob identification systemequipment. The main tasks of this section are described as follows: Design imageacquisition device, improved the acquisition device according to practice, choosethe appropriate image acquisition equipment by calculating the resolution, designimage acquisition methods according to the principles of optics, design the processof the system.(2) Image acquisition and pre-processing. This section includes designdatabase collection system and collecting image data, calibrate the image dataaccording to the time it captured, design the image sharpness evaluation algorithm,extract manually ring images depending on the image acquisition time.(3) Region of interest(ROI) image extraction. This section includes: extractthe desired MASK image based on K-means, get the stable MASK by iterative,designed resolution algorithm according to the left and right hand image features,extract the region of interest area based on the MASK image.(4) Image feature extraction and recognition. Design and implement the imagefeature extraction by Competitive code and matching methods on the handimagines. With the hand imagines database, we do the experiments and analyze the results of the experiments and draw our conclusions.Doorknob hand recognition system described in this paper contribute to thebiometric identification system growth. In this paper, a preliminary studydemonstrates the feasibility of the system, but there is room to improve. Furtherstudy could be carried in improving image acquisition equipment, imagepre-processing and control part of the system. It is easy to use. It achieveautomatic identification when the user hold the doorknob. It then determinewhether the user has access privileges. It can be widely used in various types ofaccess control systems.