In this paper, contactless palm and finger detection for biometric fingerprint verification/identification process with mobile devices is considered. In order to speed up the border checking verification process, we focus on capturing the whole palm in order to extract each fingertip instead of successively capturing each fingertip. The workflow comprises palm detection in order to detect the skin region within the image prior to detection of fingertips. A machine learning based algorithm with Aggregated Channel Features (ACFs) adopted for palm detection is considered. Furthermore, a geometric shape based approach for fingertip detection has been designed to reconstruct long lines along fingers. Results demonstrate the performance of both algorithms.