To treat a color image in a holistic manner, we take a unique approach to color image processing. In previous work we
have proposed a new feature image of which pixel holds the number of frequency of color vectors. This feature image
that we call Frequency Image is made from a special color histogram of an image and presents a distribution of
frequency of color. In this paper, first, we review the basic idea of Frequency Image and present a new analysis of this
image. Next, we explain the effective applications such as color edge detection, color uniformity inspection, focusing
and local exposure compensation. Then we propose a new approach to color image segmentation and demonstrate some
experimental results. Finally, we discuss some issues and advantages of using the Frequency Image. A Frequency Image
is useful to reduce the dimension of an original color image and to arrange a classification by the frequency of color
vectors. Therefore we can utilize this image effectively in various color image-processing applications.
This paper proposes a new method for improving improper exposure images. Disappearance of color information and
deterioration of brightness and contrast are occurred in images when images are taken under a bad condition such as
backlights. Generally, improper exposure images have the feature that the color difference is small, and color frequency
of them is larger than that of the proper exposure image. In this method, this feature is extracted by using a new color
histogram space based on human perception, and improve over or under exposure images visibility.
Visual tracking could be treated as target state representation and target state inference problem in an image sequence. Moreover, in cluttered and dynamic environments the better probabilities of accurate tracking depend on richer representation and more robust inference. Target state representation could be considered as color segmentation, contour detection and position mark. Target state inference could be treated as an evaluation from old states to new one in fuzzy logic at every step of an image sequence. This paper presents a special tracking system based on factored sampling model in order to resolve difficult and complicated visual tracking problem, such as a changing of target’s representation, a clutter of environments and an interaction of target and camera. This tracking system is applied to changeful target tracking by handling the related information to sample-set between every two time-steps in an image sequence and implemented in real time system at around 20Hz with 640*480 pixels image. Specially, color and position distributions of a target have been used in this system to estimate the target situation. The results show the robust, real-time system is able to track a target with enough accuracy to automatically control the camera’s pan, tilt and zoom in order to remain the object centered in the field of vision.