Highlight and Shading Invariant Color Image Segmentation Using Simulated Annealing
نویسندگان
چکیده
Color constancy in color image segmentation is an important research issue. In this paper we develop a framework, based on the Dichromatic Re ection Model for asserting the color highlight and shading invariance, and based on a Markov Random Field approach for segmentation. A given RGB image is transformed into a R'G'B' space to remove any highlight components, and only the vector-angle component, representing color hue but not intensity, is preserved to remove shading e ects. Due to the arbitrariness of vector angles for low R'G'B' values, we perform a Monte-Carlo sensitivity analysis to determine pixel-dependent weights for the MRF segmentation. Results are presented and analyzed.
منابع مشابه
Stochastic Nested Aggregation for Images and Random Fields
Image segmentation is a critical step in building a computer vision algorithm that is able to distinguish between separate objects in an image scene. Image segmentation is based on two fundamentally intertwined components: pixel comparison and pixel grouping. In the pixel comparison step, pixels are determined to be similar or different from each other. In pixel grouping, those pixels which are...
متن کاملColor Invariant Snakes
Snakes provide high-level information in the form of continuity constraints and minimum energy constraints related to the contour shape and image features. These image features are usually based on intensity edges. However, intensity edges may appear in the scene without a material/color transition to support it. As a consequence, when using intensity edges as image features, the image segmenta...
متن کاملColor Image Segmentation Using MRF Model and Simulated Annealing
In this paper color image segmentation is accomplished using MRF model. The problem is formulated as a pixel labeling and the true labels are modeled as the MRF model. The observed color image is assumed to be the degraded version of the true labels. We assume the degradation to be Gaussian distribution. The label estimates are obtained by using Bayesian framework and MAP criterion. The (I1, I2...
متن کاملUnsupervised Color Image Segmentation using MRF Models to Preserve Weak Edges
In this paper, an unsupervised color image segmentation scheme is proposed using homotopy continuation method. Different variants of MRF model is used to preserve both strong and weak edges. A Compound Markov Random Field (COMRF) model with Bi-level Binary Line Fields is proposed. The scheme is specifically meant to preserve weak edges besides the well defined strong edges.The proposed scheme i...
متن کاملUsing a Color Reflection Model to Separate Highlights from Object Color
Current methods for image segmentation are confused by artifacts such as highlights, because they are not based on any physical model of these phenomena. In this paper, we present an approach to color image understanding that accounts for color variations due to highlights and shading. Based on the physics of reflection by dielectric materials, such as plastic, we show that the color of every p...
متن کامل