A personal authentication method is proposed by integrating palmar geometry with the palmar and finger flexion crease analysis. A 900 x 900 image of either palm, placed freely on the flat transparent plate, is captured. Feature extraction involves: area, width and perimeter of the palm; areas, perimeters, skeletal axes and their lengths of the four fingers; shape factors of the palm and the fingers derived from the areas and the perimeters; aspect ratios; lengths of all of the finger flexion creases; intersecting points of the finger axes and the finger flexion creases; intersecting points of the finger axes and the major palmar flexion creases, those are prominent and typically classified into the thenar crease, the proximal transverse crease and the distal transverse crease. Some minor or secondary flexion creases are additionally detected. Orientation of the crease at each point of intersection is also detected. These metrics define the feature vectors for matching. We have tested the method on a limited set of palm images collected in a laboratory environment. Matching results, especially featured the oriented intersecting points of palmar creases, are encouraging. This integration with the palmar feature extraction will contribute to a more robust and reliable authentication system.