Texture is an image consisting of repeated or random arrangements of simple objects. Reconition and discrimination of textures are important aims of image processing, as well as recognition of object shapes. "Texture modeling" is a texture characteristics description method that considers a model that a texture is an arrangement of grains derived from certain primitives, and that estimates the primitives from the texture under some assumption on the model. This research realizes a simple description of the characteristics of textures, texture descrimination, etc.

We consider a model that a texture is an arrangement of grains derived from one or a few primitives. A texture is characterized using this model by the following three parameters:

• Shape of primitives,
• Derivation of grains, and
• Spatial arrangement of grains (point configuration).

This idea is one of the structural approaches, which describe rules of repetitive structures in textures, and we call this idea "Primitive, Grain and Point Configuration (PGPC)" texture model.

If we introduce an assumption on one of the above three parameters of this model, we can estimate the others. We investigates the estimation of texture characteristics using the mathematical morphology, which is a fundamental theory of shape analysis, and stochastic optimization methods to obtain the most suitable parameters.

Optimization of image processing filters is an application of the texture feature estimation. Applying an image processing filter with parameters fit to the estimated texture features separates noise from the features contained in the target texture and achieves effective noise removal.

Modification of the estimated texture features enables the modification of local and/or global features of the target texture and the generation of a new texture by mixing different features extracted from two different textures. We apply this method to the research of human kansei on images. This research investigates influences of texture features to kansei by generating mixed textures and measuring human kansei on them.

We also organize le Club des Morphologistes Mathématiques du Japon, which is a relationship of researchers who have interests in mathematical morphology in various research area. We organize special sessions on mathematical morphology in various conferences, publish reviews and have review talks, and obtain research budgets, based on le Club.

Selected publications

Texture feature estimation and application to image processing filters

• Y. Hanada, M. Muneyasu, and A. Asano, "Effectiveness of genetic multistep search in unsupervised design of morphological filters for noise removal," IPSJ Transactions on Mathematical Modeling and its Applications, in press.
• H. Okuno, Y. Hanada, M. Muneyasu, and A. Asano, "An unsupervised optimization of structuring elements for noise removal using GA," IEICE Trans. Fundamentals, in press.
• Y. Hanada, H. Okuno, M. Muneyasu, and A. Asano, "Application of Genetic Multi-Step Search to Unsupervised Design of Morphological Filters for Noise Removal," Proc. 2009 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS2009) 566-569 (2009. 12).
• A. Asano, M. Saiki, and M. Fujio, "Texture Analysis Based on Mathematical Morphology and MDL Principle," Proc. 2009 International Workshop on Smart Info-Media Systems in Asia (SISA2009) 155-159 (2009. 10).
• H. Okuno, Y. Hanada, M. Muneyasu, and A. Asano, "An Unsupervised Optimization of Structuring Elements for Noise Removal Using GA," Proc. 2009 International Workshop on Smart Info-Media Systems in Asia (SISA2009) 144-149 (2009. 10).
• A. Fujiki, A. Asano, and M. Muneyasu, "Unsupervised optimization of morphological filters for noise removal in texture images," Proc. Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2006) 1794-1799 (2006. 9).
• A. Fujiki, A. Asano, and M. Muneyasu, "Unsupervised structuring element optimization of morphological opening for texture images," Proc. 2006 International Symposium on Nonlinear Theory and its Applications (NOLTA2006), 711-714 (2006. 9).
• A. Fujiki, T. Hashimoto, M. Muneyasu, and A. Asano, "A design of window shapes and weights in weighted median filters for texture images," Proc. 2005 International Symposium on Intelligent Signal Processing and Communications Systems (ISPACS 2005), 665-668 (2005. 12).
• A. Asano, Y. Kobayashi, C. Muraki, and M. Muneyasu, "Optimization of gray scale morphological opening for noise removal in texture images," Proc. 47th IEEE International Midwest Symposium on Circuits and Systems (MWSCAS2004), 1, 313-316 (2004. 7).
• A. Asano, M. Miyagawa, and M. Fujio, "Morphological texture analysis using optimization of structuring elements," Geometry, Morphology, and Computational Imaging, Springer LNCS 2616, 141-152 (2003. 4).
• A. Asano, J. Endo, and C. Muraki, "Multiprimitive texture analysis using cluster analysis and morphological size distribution," IEICE Trans. Fundamentals, E85-A, 9, 2180-2183 (2002. 9).

Texture generation

• L. Li, A. Asano, and C. Muraki Asano, "Evaluation of Human Visual Impressions in Gray Scale Textures Using Morphological Manipulation," Proc. 8th International Conference on Hybrid Intelligent Systems (HIS2008), 114-119 (2008. 9).
• C. Muraki Asano, A. Asano, T. Fujimoto, "Morphological Texture Manipulation and Human Visual Impressions," Proc. International Conference on Kansei Engineering and Emotion Research 2007 (KEER2007), F-8 (2007. 10). [Excellent Paper Award]
• A. Asano, Y. Kobayashi, and C. Muraki, "Intersize correlation of grain occurrences in textures and its application to texture regeneration," Mathematical Morphology: 40 years On; Proc. 7th International Symposium on Mathematical Morphology (ISMM'05), 357-366 (2005. 4).
• Y. Kobayashi and A. Asano, "Modification of spatial distribution in Primitive and Point Configuration texture model," Proc. 13th Scandinavian Conference on Image Analysis, Springer LNCS 2749, 877-884 (2003. 7).

Reviews on mathematical morphology

• A. Asano, M. Fujio, H. Nobuhara, M. Muneyasu, and C. Muraki Asano, "Mathematical morphology - fundamentals and advances," Proc. Joint 3rd International Conference on Soft Computing and Intelligent Systems and 7th International Symposium on advanced Intelligent Systems (SCIS & ISIS 2006), 1630-1635 (2006. 9) [invited talk].
• A. Asano, "Mathematical morphology and its applications," Proc. Information and Communication Technology Seminar 2005, 1-9 (2005. 8). [invited keynote speech]