Biometrics has evolved in the past decades and trusted by everyone in the world. Biometrics are highly secured when compared to passwords and pins. The main intention of this research is to exhibit novel biometrics named "Hand Wrist Biometrics" and demonstrate feasibility of feature matching between peoples hand wrist. Hand wrist biometrics is an alternate way of recognizing the individuality. Our most important contribution of this research is to bring up novel hand wrist biometrics to the world. Hand wrist has a distinctive feature to recognize and identify the objects. Preprocessing of hand wrist uses a robust technique canny edge detector which extracts real ridge lines of hand wrist. To detect objects in hand wrist, This study approaches a SURF to speed up robust feature to identity unique interest points which can be used for identification. SURF has inbuilt features to detect objects with good accuracy. Feature matching is based upon the location of identified interest point features. We investigated an experiment with how the matching process happening between the two-hand wrist. This paper also leads a performance evaluation of Hand Wrist. We also demonstrated the matching possibility of hand wrist using SURF interest points. This study aims to illuminates that hand wrist also having a unique feature that are very helpful for identification. © 2018 IAEME Publication.