  The Active Shape Model (ASM) is one of the most popular local texture models
for face alignment. It applies in many fields such as locating facial features
in the image, face synthesis, etc. However, the experimental results show that
the accuracy of the classical ASM for some applications is not high. This paper
suggests some improvements on the classical ASM to increase the performance of
the model in the application: face alignment. Four of our major improvements
include: i) building a model combining Sobel filter and the 2-D profile in
searching face in image; ii) applying Canny algorithm for the enhancement edge
on image; iii) Support Vector Machine (SVM) is used to classify landmarks on
face, in order to determine exactly location of these landmarks support for
ASM; iv)automatically adjust 2-D profile in the multi-level model based on the
size of the input image. The experimental results on Caltech face database and
Technical University of Denmark database (imm_face) show that our proposed
improvement leads to far better performance.
