Recognizing Color Patterns Irrespective of Viewpoint and Illumination

نویسندگان

  • Florica Mindru
  • Theo Moons
  • Luc Van Gool
چکیده

New invariant features are presented that can be used for the recognition of planar color patterns such as labels , logos, signs, pictograms, etc., irrespective of the viewpoint or the illumination conditions, and without the need for error prone contour extraction. The new features are based on moments of powers of the intensities in the individual color bands and combinations thereof. These moments implicitly characterize the shape, the intensity and the color distribution of the pattern in a uniform manner. The paper gives a classiication of all functions of such moments which are invariant under both aane deformations of the pattern (thus achieving viewpoint invari-ance) as well as linear changes of the intensity values of the color bands (hence, coping with changes in the irradiance pattern due to diierent lighting conditions and/or viewpoints). The discriminant power and clas-siication performance of the new invariants for color pattern recognition is tested on a data set of images of real, outdoors advertising panels. A comparison to moment invariants presented in literature is included as well.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Color-based Moment Invariants for Viewpoint and Illumination Independent Recognition of Planar Color Patterns

This paper contributes to the viewpoint and illumination independent recognition of planar color patterns such as labels, logos, signs, pictograms, etc. by means of moment invariants. It introduces the idea of using powers of the intensities in the different color bands of a color image and combinations thereof for the construction of the moments. First, a complete classification is made of all...

متن کامل

View and Illumination Invariant Object Classification Based on 3D Color Histogram Using Convolutional Neural Networks

Object classification is an important step in visual recognition and semantic analysis of visual content. In this paper, we propose a method for classification of objects that is invariant to illumination color, illumination direction and viewpoint based on 3D color histogram. A 3D color histogram of an image is represented as a 2D image, to capture the color composition while preserving the ne...

متن کامل

Model Estimation for Photometric Changes of Outdoor Planar Color Surfaces Caused by Changes in Illumination and Viewpoint

In this paper we compare different ways of representing the global photometric changes in image intensities caused by changes in illumination and viewpoint, aiming at a balance between goodness-of-fit and low complexity. A series of model selection tests are performed for the case of outdoor imagery consisting of several views of several instances of billboards taken under different viewing ang...

متن کامل

Visual learning and object verification with illumination invariance

This paper describes a method for recognizing partially occluded objects to realize a bin-picking task under different levels of illumination brightness by using the eigen-space analysis. In the proposed method, a measured color in the RGB color space is transformed into the HSV color space. Then, the hue of the measured color, which is invariant to change in illumination brightness and directi...

متن کامل

Modified CLPSO-based fuzzy classification System: Color Image Segmentation

Fuzzy segmentation is an effective way of segmenting out objects in images containing both random noise and varying illumination. In this paper, a modified method based on the Comprehensive Learning Particle Swarm Optimization (CLPSO) is proposed for pixel classification in HSI color space by selecting a fuzzy classification system with minimum number of fuzzy rules and minimum number of incorr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 1999