Quantifying the motion and deformation of cells through image sequences obtained with microscopy is a recurrent task. Firstly, the clustering cells contour of blurred image is separated and a cell boundary feature extraction algorithm based on binary fitting energy (BFE) region representative is implemented. BFE driven model allows for an excellent approximation of smooth region at global scope. Then contour strategy for digital cell image by local BFE under variational model framework is presented. It also combined a robust convergence criteria and a scheme to determine the optimal time-step for the numerical solution of the level set equation. It is more accurate than the classical contour extraction algorithm under variational model framework, for bio-inspired cell contour extraction corrupted by interference, with blurred edges. Experimental results tested by different low visual quality of tissue cells demonstrate good performances of the BFE method for tracking quantification of cell motility.