The Intrinsic Safety Type Of Mine Iris Identification System Research

As now the mine safety production is emphasized highly, the requirement for the safety management system is higher and higher. However, management is always based on enough acquaintance of underground situation. So it is important to identify staff efficiently. Iris recognition avoids that other biological characteristics changing more or less because of external conditions leads to error recognizing, so it has incomparable advantage under the environment like mining underground. Mining intrinsic safety iris recognition system, suitable to mining safety management system, is the research orientation of this paper.At the beginning of the paper, it introduces various kinds of biometric recognition technology, and expounds briefly the advantage of iris recognition technology in underground recognition system. On the whole development history of iris recognition technology and the current research status at home and abroad, paper analyses the technology playing an important role in the mine underground staff management system and the inevitable trend of the tech being used widely at coal mine.In consideration of the work environment for the system being underground, it is designed as intrinsic safety. Images are captured by CV-A436black and white camera, transmitted via electric cable and optical fiber underground. KJD31mining flameproof and intrinsic safety computer and KDW28-18mining intrinsic safety power supply are also important parts of the system. This system has the advantage of small size, low cost, consisting of intrinsic safety power supply, camera and industrial control computer. It is an intrinsic safety recognition system.It introduces the feature, structure and working principle of iris recognition technology. From iris images preprocessing, such as iris locating, normalization and iris enhancing, to feature extraction and encoding of iris images, it gives the algorithm of iris recognition, and builds image quality assessment system to filter those images gray level distribution, blurring or hiding to increase identification accuracy and speed. It also uses multichannel Gabor filter function to analyze the iris texture information, and collects iris feature to enhance the utilization of iris information and veracity of recognition.The experiment results indicated that the iris recognition system the paper designed had a good recognizing result, with great performance in precision, recognition speed and robustness. At the same time, because of no complicated hardware in the system, the algorithm can be easily transplanted to normal computer just with a camera meet the requirement for capturing iris images. Working on the MATLAB platform, it can run well under various environments.