Patent ID: 7068843

Claim:
A method for extracting and matching gesture features of an image, comprising the steps of: (A) capturing an input gesture image; (B) determining a closed curve formed by a binary contour image of the gesture image by preprocessing the gesture image; (C) drawing a curvature scale space (CSS) image of the gesture image based on the closed curve; (D) determining feature parameters of a plurality of sets of the gesture image by extracting first plural peaks from the CSS image as basis points, wherein each peak is a local maximum larger than a critical value and each feature parameter of the sets of the gesture image is obtained by performing the steps of: (D1) calculating all sets of the peaks in the CSS image to form a coordinate-peak set: {( u i ,σ i )} i=1, . . . ,N Original ={( u 1 ,σ 1 ), ( u 2 ,σ 2 ), . . . ,( u j ,σ j ), . . . ,( u N ,σ N )}, where N is the number of detected peaks in the CSS image; (D2) taking u j as a basis point to normalize the coordinate-peak set through a circular rotation as a normalized coordinate-peak set: {( u i ,σ i )} i=1, . . . ,N Normalized ={(0,σ j ), . . . , ( u j+1 −u j ,σ j+1 ), . . . ,(1 +u 1 −u j ,σ j ), . . . , (1 +u j−1 −u j ,σ j−1 )} where u 1 <u 2 < . . . <u j < . . . <u N and u j is a u-axis coordinate having a maximal peak in the coordinate-peak set; and (D3) selecting first T largest peaks as basis points to normalize the coordinate-peak set for obtaining T sets of normalized feature parameter F I ={{(u i I ,σ i I )} i=1, . . . ,N t−Normalized |t=1,2, . . . ,T}, where I is the input gesture image; and (E) comparing each feature parameter obtained in step (d) of the sets of the gesture image with each feature parameter of a plurality of reference gesture shapes for determining a gesture shape corresponding to the gesture image.