Weighted map for reflectance and shading separation using a single image

Sung Hsien Hsieh; Chih Wei Fang; Te Hsun Wang; Chien Hung Chu; Jenn Jier James Lien

doi:10.1007/978-3-642-12297-2_9

Weighted map for reflectance and shading separation using a single image

Sung Hsien Hsieh, Chih Wei Fang, Te Hsun Wang, Chien Hung Chu, Jenn Jier James Lien

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

Abstract

In real world, a scene is composed by many characteristics. Intrinsic images represent these characteristics by two components, reflectance (the albedo of each point) and shading (the illumination of each point). Because reflectance images are invariant under different illumination conditions, they are more appropriate for some vision applications, such as recognition, detection. We develop the system to separate them from a single image. Firstly, a presented method, called Weighted-Map Method, is used to separate reflectance and shading. A weighted map is created by first transforming original color domain into new color domain and then extracting some useful property. Secondly, we build Markov Random Fields and use Belief Propagation to propagate local information in order to help us correct misclassifications from neighbors. According to our experimental results, our system can apply to not only real images but also synthesized images.

Original language	English
Title of host publication	Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers
Pages	85-95
Number of pages	11
Edition	PART 3
DOIs	https://doi.org/10.1007/978-3-642-12297-2_9
Publication status	Published - 2010 Dec 29
Event	9th Asian Conference on Computer Vision, ACCV 2009 - Xi'an, China Duration: 2009 Sep 23 → 2009 Sep 27

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	5996 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	9th Asian Conference on Computer Vision, ACCV 2009
Country/Territory	China
City	Xi'an
Period	09-09-23 → 09-09-27

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-12297-2_9

Cite this

Hsieh, S. H., Fang, C. W., Wang, T. H., Chu, C. H., & Lien, J. J. J. (2010). Weighted map for reflectance and shading separation using a single image. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers (PART 3 ed., pp. 85-95). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5996 LNCS, No. PART 3). https://doi.org/10.1007/978-3-642-12297-2_9

Hsieh, Sung Hsien ; Fang, Chih Wei ; Wang, Te Hsun ; Chu, Chien Hung ; Lien, Jenn Jier James. / Weighted map for reflectance and shading separation using a single image. Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3. ed. 2010. pp. 85-95 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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title = "Weighted map for reflectance and shading separation using a single image",

abstract = "In real world, a scene is composed by many characteristics. Intrinsic images represent these characteristics by two components, reflectance (the albedo of each point) and shading (the illumination of each point). Because reflectance images are invariant under different illumination conditions, they are more appropriate for some vision applications, such as recognition, detection. We develop the system to separate them from a single image. Firstly, a presented method, called Weighted-Map Method, is used to separate reflectance and shading. A weighted map is created by first transforming original color domain into new color domain and then extracting some useful property. Secondly, we build Markov Random Fields and use Belief Propagation to propagate local information in order to help us correct misclassifications from neighbors. According to our experimental results, our system can apply to not only real images but also synthesized images.",

author = "Hsieh, {Sung Hsien} and Fang, {Chih Wei} and Wang, {Te Hsun} and Chu, {Chien Hung} and Lien, {Jenn Jier James}",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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Hsieh, SH, Fang, CW, Wang, TH, Chu, CH & Lien, JJJ 2010, Weighted map for reflectance and shading separation using a single image. in Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 5996 LNCS, pp. 85-95, 9th Asian Conference on Computer Vision, ACCV 2009, Xi'an, China, 09-09-23. https://doi.org/10.1007/978-3-642-12297-2_9

Weighted map for reflectance and shading separation using a single image. / Hsieh, Sung Hsien; Fang, Chih Wei; Wang, Te Hsun; Chu, Chien Hung; Lien, Jenn Jier James.

Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3. ed. 2010. p. 85-95 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5996 LNCS, No. PART 3).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Hsieh SH, Fang CW, Wang TH, Chu CH, Lien JJJ. Weighted map for reflectance and shading separation using a single image. In Computer Vision, ACCV 2009 - 9th Asian Conference on Computer Vision, Revised Selected Papers. PART 3 ed. 2010. p. 85-95. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). https://doi.org/10.1007/978-3-642-12297-2_9

Weighted map for reflectance and shading separation using a single image

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