An Effective Method for Illumination-Invariant Representation of Color Images

Horiuchi, Takahiko; Ibrahim, Abdelhameed; Kadoi, Hideki; Tominaga, Shoji

doi:10.1007/978-3-642-33868-7_40

Computer Vision – ECCV 2012. Workshops and Demonstrations

2012

DOI: 10.1007/978-3-642-33868-7_40

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An Effective Method for Illumination-Invariant Representation of Color Images

Takahiko Horiuchi

Abdelhameed Ibrahim

Hideki Kadoi

et al.

Abstract: This paper proposes a method for illumination-invariant representation of natural color images. The invariant representation is derived, not using spectral reflectance, but using only RGB camera outputs. We suppose that the materials of target objects are composed of dielectric or metal, and the surfaces include illumination effects such as highlight, gloss, or specularity. We preset the procedure for realizing the invariant representation in three steps: (1) detection of specular highlight, (2) illumination c… Show more

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Cited by 2 publications

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Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

Chen¹,

Meng²,

Lü³

et al. 2019

Computer and Computing Technologies in Agriculture X

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With the application of IOT technology in maize disease images for monitoring and collecting, timely detection of the types and characteristics of identification of disease has become a hot research in the diagnosis and treatment of diseases and insect pests. In order to improve the recognition accuracy of maize leaf, achieve rapid diagnostic purposes, this paper takes the leaf spot of maize gray leaf spot and image as the research object, use the computer image processing technology is studied on the effective segmentation and recognition of color and shape features. The genetic algorithm was adopted to optimize the selection of maize disease images real-time filtering; 3*3 mode noise suppression of the image selected by value smoothing; then select the HSV component of the color feature extraction of the disease; the maximum between class variance (OTSU) disease shape character segmentation and recognition. The results show that, based on genetic algorithm optimization based on image In HSV and Otsu method can be more accurate segmentation and recognition of the disease of color and shape features, and enhance the real-time and accuracy of the image of maize disease detection and recognition and oriented under the condition of things plant diseases and insect pests of maize and provide technical support.

show abstract

Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

Chen¹,

Meng²,

Lü³

et al. 2019

Computer and Computing Technologies in Agriculture X

View full text Add to dashboard Cite

show abstract

Color Invariant Representation and Applications

Ibrahim

Horiuchi

Tominaga

et al. 2017

Handbook of Research on Machine Learning Innovations and Trends

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Illumination factors such as shading, shadow, and highlight observed from object surfaces affect the appearance and analysis of natural color images. Invariant representations to these factors were presented in several ways. Most of these methods used the standard dichromatic reflection model that assumed inhomogeneous dielectric material. The standard model cannot describe metallic objects. This chapter introduces an illumination-invariant representation that is derived from the standard dichromatic reflection model for inhomogeneous dielectric and the extended dichromatic reflection model for homogeneous metal. The illumination color is estimated from two inhomogeneous surfaces to recover the surface reflectance of object without using a reference white standard. The overall performance of the invariant representation is examined in experiments using real-world objects including metals and dielectrics in detail. The feasibility of the representation for effective edge detection is introduced and compared with the state-of-the-art illumination-invariant methods.

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An Effective Method for Illumination-Invariant Representation of Color Images

Cited by 2 publications

References 10 publications

Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

Research on Color and Shape Recognition of Maize Diseases Based on HSV and OTSU Method

Color Invariant Representation and Applications

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