Dong-Guk Hwang

Frankle-McCann Retinex by Shuffling

In this paper, our aim is to present an alternative to the ratio-product term of Frankle-McCann Retinex by manipulating shifting directions and the number of iterations, which is a major obstacle in applications, keeping the quality of the result images. For this, we focus on replacing the shifting mechanism with a symmetrical shuffling method that partitions all given regions in each channel image into two parts per region and then exchanges each other in two pre-determined directions. This processing has the advantage in that there is no need to consider shifting directions at a step, so the complexity of the algorithm is reduced, except for the shuffling cost. From the experiments on Barnard’s four datasets, the results showed that our expectation can be met by the proposed method.

Analysis of Color Constancy Methods for Recovering Skin Color Independent of Illuminants

The skin color has been used as important cues in the systems for detecting or recognizmg the face. However, the color difference in images under different illuminants makes it difficult to find out the skin in these systems. For solving the problem, this paper proposes a method of recovering skin colors based on well-known color constancy approaches, such as Retinex, Gray World, White Patch, and Simplified Horn. To acquire experimental images under the colored scene illumination, the effects of colored illuminants were added to source images. Next, result images, having the corrected skin color by the constancy methods, were derived from the source images. The experiment results showed that most of the skin colors in our experiments were recovered into some steady range in the color space, and that Gray World had higher performance than the other methods compared.

Production of Low-illuminated Image Sets based on Spectral Data for Color Constancy Research

Abstract Most methods of color constancy, which is the ability to determine the object color regardless of the scene illuminant, have failed to meet our expectation of their performance especially about low-illuminated scenes. Some methods with high performance need to be developed, but we must, above all else, obtain experimental images for analyzing the required circumstances or evaluating the methods. Therefore, the paper produces new sets of images so that they can be used in the development of color constancy methods suitable for low-illuminated scenes. These sets are composed of two parts: one part of images which are synthesized with spectral power distribution(SPD) of illuminants, spectral reflectance curve of reflectances, and sensor response functions of camera; the other part of images where the intensity of each image is adjusted at the uniform rate. In an experiment, the use of the sets takes an advantage that its result images are analyzed and evaluated quantitatively as their ground truth data are known in advance.

Design of a reversible PLD architecture

Reversible gate is a circuit that has the same number of inputs and outputs satisfying one-to-one mapping between the vectors of input and output. So far several logic synthesis methods for reversible logic have been proposed, however, they are not able to synthesize a reversible function with input and output of arbitrary width in a constructive manner based on building blocks and interconnect. This paper proposes a new reversible PLD(programmable logic device) architecture that enables any reversible function to be implemented by cascading the building blocks, or logic units through interconnect, and fits well on arithmetic circuits in particular. Also, a new reversible gate, T2F gate, is suggested and adopted in the proposed reversible PLD architecture. Both reversible PLD and T2F gate offer significant alternative view on reversible logic synthesis.

Acquisition of Intrinsic Image by Omnidirectional Projection of ROI and Translation of White Patch on the X-chromaticity Space

Algorithms for intrinsic images reduce color differences in RGB images caused by the temperature of black-body radiators. Based on the reference light and detecting single invariant direction, these algorithms are weak in real images which can have multiple invariant directions when the scene illuminant is a colored illuminant. To solve these problems, this paper proposes a method of acquiring an intrinsic image by omnidirectional projection of an ROI and a translation of white patch in the -chromaticity space. Because it is not easy to analyze an image in the three-dimensional RGB space, the -chromaticity is also employed without the brightness factor in this paper. After the effect of the colored illuminant is decreased by a translation of white patch, an invariant direction is detected by omnidirectional projection of an ROI in this chromaticity space. In case the RGB image has multiple invariant directions, only one ROI is selected with the bin, which has the highest frequency in 3D histogram. And then the two operations, projection and inverse transformation, make intrinsic image acquired. In the experiments, test images were four datasets presented by Ebner and evaluation methods was the follows: standard deviation of the invariant direction, the constancy measure, the color space measure and the color constancy measure. The experimental results showed that the proposed method had lower standard deviation than the entropy, that its performance was two times higher than the compared algorithm.

Shadow Detection Using Linearity of Shadow Brightness from a Single Natural Image

This paper proposes a novel approach to shadow detection from a single natural image regardless of orientation and type of light sources. This approach is based on the assumption that shadow brightness changes linearly, and the axiom that a region cast shadow on is darker than that not having shadow under the same environment. Firstly, candidates for shadow are extracted by preprocessing. Then, they are quantized to replace the similar values with a representative value because of the more quantization steps of a pixel brightness, the higher linear independency among the neighboring pixels. Finally, shadows are detected according to linear independency of shadow brightness based on the assumption. The experimental results showed the proposed approach can robustly detect umbra as well as self-shadow and penumbra cast on a single-colored background.