This paper presents the development of a new algorithm for Gaussian based color image enhancement system. The algorithm has been designed into architecture suitable for FPGA/ASIC implementation. The color image enhancement is achieved by first convolving an original image with a Gaussian kernel since Gaussian distribution is a point spread function which smoothes the image. Further, logarithmdo...

In this paper, we present a method to represent achromatic and chromatic image signals independently for content-based image indexing and retrieval for image database applications. Starting from an opponent colour representation, human colour vision theories and modern digital signal processing technologies are applied to develop a compact and computationally e-cient visual appearance model for...

Color image segmentation is an important but still open problem in image processing. In this paper, we propose a method for this problem by integrating the spatial connectivity and color feature of the pixels. Considering that an image can be regarded as a dataset in which each pixel has a spatial location and a color value, color image segmentation can be obtained by clustering these pixels in...

In this paper we present a new opponent color system which imitates some of the known color processing neural cells established by electrophysiological recordings. We describe the benefits of this system to image processing tasks. The opponent color model is embedded in an active vision system to improve the systems fixation and recognition capabilities. This is done by removing illumination ef...

Article history: Available online 8 February 2013 Feature extraction and representation is one of the most important issues in the contentbased image retrieval. In this paper, we propose a new content-based image retrieval technique using color and texture information, which achieves higher retrieval efficiency. Firstly, the image is transformed from RGB space to opponent chromaticity space, an...

The proposed model introduces an improvement over some other basic color classification techniques which are considered more challenging to color segmentation methods. In color vision systems require a first step of classifying pixels in a given image into a discrete set of color classes. In this paper we describe a human perception based approach to pixel color segmentation which applied in co...

This paper describes a comparative study of color image segmentation for various color spaces such as RGB, YUV, XYZ, Lab, HSV, YCC and CMYK using Dynamic Histogram based Rough Fuzzy C Means (DHRFCM). The proposed algorithm DHRFCM is based on modified Rough Fuzzy C Means (RFCM), which is further divided into three stages. In the pre-processing stage, convert RGB into required color space and the...

The Laplace-Beltrami operator is an extension of the Laplacian from flat domains to curved manifolds. It was proven to be useful for color image processing as it models a meaningful coupling between the color channels. This coupling is naturally expressed in the Beltrami framework in which a color image is regarded as a two dimensional manifold embedded in a hybrid, five-dimensional, spatial-ch...