Research of uniqueness detection technology for in-pit coal mine personnel
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摘要: 通过分析掌纹、指纹、虹膜、人脸、步态、声纹等生物特征识别技术的特点以及煤矿现场对入井人员生物特征的影响,指出虹膜识别、人脸识别、步态识别、声纹识别适用于煤矿入井人员唯一性检测;提出了一种基于人员定位和生物特征识别的煤矿入井人员唯一性检测技术方案,将生物特征识别技术嵌入人员定位系统,利用人员定位识别卡实现识别卡数量及人员身份的唯一性检测;指出煤矿入井人员唯一性检测技术的研究关键点是严重污染人脸的识别算法、对设备遮挡情况下人员步态图像的采集及对混入人员语音信号的煤矿现场噪声消除算法。Abstract: Based on analysis of characteristics of biometric feature recognition technologies by palmprint, fingerprint, iris, face, gait and voiceprint and impacts of coal mine field on biometric features of in-pit coal mine personnel, it was pointed out that iris recognition, face recognition, gait recognition and voiceprint recognition were applicable to uniqueness detection of in-pit coal mine personnel. A scheme of uniqueness detection of in-pit coal mine personnel was proposed based on personnel location and biometric feature recognition, which embedded biometric feature recognition technology into personnel location system and used personnel location identification cards to achieve uniqueness detection of the card number and personnel identity. Key points of research on uniqueness detection technology of in-pit coal mine personnel were pointed out, which were recognition algorithms of seriously-stained face, acquisition algorithms of personnel gait images under the condition of equipment occlusion and elimination algorithms of noise in coal mine field mixing into personnel voice signals.
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