A novel recognition method for color objects different illuminations

• Autorzy: Wang J. , Lin Z. , Zhu J.
• Języki publikacji: EN

Abstrakty

EN

Color images depend on the scene illumination, but these image colors are not stable features for object recognition. We develop an algorithm that transforms color into its normal form such that is invariant to different illuminations. Since the normalization process is to make color image compact, solors distorted in different ways from the same object due to illumination change will all be compacted to their most compact feom and become similar. After compaction process, the histograms for the same objects under different illuminations are very similar. The recognition can be performed by simple matching method. A set of experiments on complex scenes under various other reported techniques for color normalization.

Słowa kluczowe

EN

affine transform; color image compaction; histogram; invariant image matching

• Wydawca: Institute of Information Technology of the Warsaw University of Life Sciences – SGGW
• Czasopismo: Machine Graphics and Vision
• Rocznik: 2001
• Tom: Vol. 10, No. 1
• Strony: 103--112
• Opis fizyczny: Bibliogr. 5 poz.

Twórcy

autor

Wang J.

• Information System Research Laboratory Division of Information Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798

autor

Lin Z.

• Information System Research Laboratory Division of Information Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798

autor

Zhu J.

• Information System Research Laboratory Division of Information Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798

Bibliografia

• [1] Healey G., Slater D.: Global color constancy: recognition of object by use of illumination-invariant properties of color distributions. J. Opt. Soc. Am. A, 11(1), 3003-3010, 1994.
• [2] Pei S. C., Lin C. N.: Image normalization for pattern recognition. Image and Vision Computing, 13(10), 711-723, 1995.
• [3] Funt B. V., Martin L.: Is matching color constancy good enough. Proc. ECCV'98, 446-459.
• [4] Wang L. Z., Healey G.: Using Zernike Moments for the illumination and geometry invariant classification of multispectral texture. IEEE Trans. IP, 7(2), 196-203, 1998.
• [5] Finlayson G. D., TianG. Y.: Color Normalization for color object recognition. Int. J. PR&AI, 13(8), 1271-1285, 1999.