Tank Farm Contractor Work Place Air Monitoring

SummaryWork plays an important part in everyday life. For people experiencing mental health problems employment may both provide a source of income, improved self-esteem and stability, and influence the course and outcomes of the disorder. Yet in many countries the work-place consistently surfaces as the context where people with mental health problems feel stigmatised and discriminated the most. This paper will review the existing evidence of stigma and discrimination in the workplace, consider the consequences of workplace stigma on the lives of people experiencing mental health problems, and discuss implications for further action.

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IRIS AND FINGER VEIN MULTI MODEL RECOGNITION SYSTEM BASED ON SIFT FEATURES

Journal of Advanced Sciences and Engineering Technologies ◽

10.32441/jaset.v1i2.119 ◽

2018 ◽

Vol 1 (2) ◽

pp. 34-44

Author(s):

Faris E Mohammed ◽

Dr. Eman M ALdaidamony ◽

Prof. A. M Raid

Keyword(s):

Iris Recognition ◽

Recognition Performance ◽

Recognition System ◽

Individual Identification ◽

Work Place ◽

Identification Process ◽

Finger Vein ◽

Noise Point ◽

Vein Recognition ◽

A New Technique

Individual identification process is a very significant process that resides a large portion of day by day usages. Identification process is appropriate in work place, private zones, banks …etc. Individuals are rich subject having many characteristics that can be used for recognition purpose such as finger vein, iris, face …etc. Finger vein and iris key-points are considered as one of the most talented biometric authentication techniques for its security and convenience. SIFT is new and talented technique for pattern recognition. However, some shortages exist in many related techniques, such as difficulty of feature loss, feature key extraction, and noise point introduction. In this manuscript a new technique named SIFT-based iris and SIFT-based finger vein identification with normalization and enhancement is proposed for achieving better performance. In evaluation with other SIFT-based iris or SIFT-based finger vein recognition algorithms, the suggested technique can overcome the difficulties of tremendous key-point extraction and exclude the noise points without feature loss. Experimental results demonstrate that the normalization and improvement steps are critical for SIFT-based recognition for iris and finger vein , and the proposed technique can accomplish satisfactory recognition performance. Keywords: SIFT, Iris Recognition, Finger Vein identification and Biometric Systems. © 2018 JASET, International Scholars and Researchers Association

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