Semiautomatic feature specification based on snakes for image morphing

Aboul Ella Hassanien; Hiroki Takahashi; Masayuki Nakajima

doi:10.1117/12.279567

30 October 1997 Semiautomatic feature specification based on snakes for image morphing

Aboul Ella Hassanien, Hiroki Takahashi, Masayuki Nakajima

Proceedings Volume 3164, Applications of Digital Image Processing XX; (1997) https://doi.org/10.1117/12.279567
Event: Optical Science, Engineering and Instrumentation '97, 1997, San Diego, CA, United States

Abstract

Recent efforts in image morphing research aim at improving both user interface and warping results. To specify feature points in tow images, the user interface takes up much time and it allows the warping specification by the user which represents very tedious work. In this paper, we propose a semi-automatic algorithm based on active contour model to specify the feature correspondence between two given images. It allows a user to extract a contour that defines a facial features such as lips, mouth, profile, etc., by specifying only endpoints of the contour around the feature that serve as the extremities of a contour. The proposal algorithm uses these two points as anchor points, and automatically computes the image information around these endpoints to provide boundary conditions. Then we optimize the contour by taking this information into account close to its extremities. During the iterative optimization process, the image forces are moving progressively from the contours extremities towards its center to define the feature. Once the feature correspondence points are paired, the intermediate images are generated by interpolating the positions of feature points linearly. The proposal algorithm helps the user to define easily the exact position of a feature. It may also reduce the time taken to establish feature correspondence between two images.

Citation Download Citation

Aboul Ella Hassanien, Hiroki Takahashi, and Masayuki Nakajima "Semiautomatic feature specification based on snakes for image morphing", Proc. SPIE 3164, Applications of Digital Image Processing XX, (30 October 1997); https://doi.org/10.1117/12.279567

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