Multilevel autoregressive models for planar shape

Masaru Tanaka; Hiroyuki Shimai; Takio Kurita; Takaomi Shigehara

doi:10.1117/12.365864

18 October 1999 Multilevel autoregressive models for planar shape

Masaru Tanaka, Hiroyuki Shimai, Takio Kurita, Takaomi Shigehara

Proceedings Volume 3808, Applications of Digital Image Processing XXII; (1999) https://doi.org/10.1117/12.365864
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

In this paper we extend the autoregressive (AR) model to the multilevel AR model with wavelet transformation, in order to get the AR coefficients at each level as a set of shape descriptors for every level. To get the multilevel AR model, we use the wavelet transformation such as Haar wavelet to a boundary data. Then real AR and complex-AR (CAR) models are adopted to the multilevel boundary data of a shape to extract the features at each level. Furthermore we present the relation of the autocorrelation coefficients between adjacent resolution levels to elucidate the relation between AR model and wavelet transformation. Some experiments are also shown for the multilevel AR and CAR models with a certain similarity measure.

Citation Download Citation

Masaru Tanaka, Hiroyuki Shimai, Takio Kurita, and Takaomi Shigehara "Multilevel autoregressive models for planar shape", Proc. SPIE 3808, Applications of Digital Image Processing XXII, (18 October 1999); https://doi.org/10.1117/12.365864

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