Biometric verification is a mean by which a person can be uniquely authenticated by evaluating some distinguishing biological traits. Fingerprinting is the ancient and the most widely used biometric authentication system today which is succeeded by other identifiers such as hand geometry, earlobe geometry, retina and iris patterns, voice waves and signature. Out of these verification methods, earlobe geometry proved to be most efficient and reliable option to be used either along with existing security system or alone for one level of security. However in previous work, the pre-processing was done manually and algorithms have not necessarily handled problems caused by hair and earing. In this paper, we present a more systematic, coherent and methodical way for ear identification using GLCM algorithm which has overcome the limitations of other successful algorithms like ICP and PCA. GLCM elucidates the texture of an image through a matrix formed by considering the number of occurrences of two pixels which are horizontally adjacent to each other in row and column. Pre-processing techniques and algorithms will be discussed and a step-by-step procedure to implement the system will be stated.