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The progress of palmprint identification has become more advanced. Efforts to produce this kind of biometric recognition have been focused on the accuracy and speed to recognize. The critical part of recognition is features representations. It must be distinctive yet produce sparse data distribution and later could be used to differentiate intended classes. This paper proposes Line Tracking that is utilized in order to detect line points to be integrated with 2D Haar Wavelet (2D HW) as the descriptors. Recognition is evaluated by matching the feature vectors to consider who own the palmprint. The provided class is constrained into only registered users. Achieved average matching score is 97.27% using 10-fold cross-validation.