Papers by Keyword: RGB Color Space

Abstract: The visual attributes of color are suitable for human perception and computer vision. A Color space is defined as a model for representing the intensity value of color. We propose a color space comparison and analysis between RGB and HSV based images retrieval. We succeed in transferring the image retrieval problem to sequences comparison and subsequently using the color sequences comparison between the color featurs of RGB and HSV to compare and analyze the images of database.

Abstract: This paper compares the performance of RGB and HSV color segmentations method in road signs detection. The road signs images are taken under various illumination changes, partial occlusion and rotational changes. The proposed algorithms using both RGB and HSV color space are able to detect the 3 standard types of colored images namely Red, Yellow and Blue. The experiment shows that the HSV color algorithm achieved better detection accuracy compared to RGB color space.

Abstract: The traditional background difference method is based on gray image. Some information is lost when color image is transformed into gray image. So it is difficult to discriminate different colors with similar gray values and easily disturbed by noise and shadows. In this paper, the background difference is based on RGB color model. It is proposed to use the average value of each pixel of the color image sequences to extract the background, and then use the three-dimensional color values of the current frame and background image to compute the difference to detect the moving objects. The proposed approach is simple and easy to implement. The experimental results show that it is more sensitive to colors and has higher accuracy and robustness than the traditional background difference method. Besides, it is more resistant to shadows.

Abstract: The hand made beaded pad is getting more and more expensive due to the increasing labor costs and its necessary to develop the beaded pads weaving machine. One of the key problems for beaded pads weaving machine developing is the beaded pad image pattern recognitions including the beads number and colors. This paper focuses on the researches of identifying the beads number and the colors of the beaded pad image. First, the beads number of the pad image is identified by threshold and calibration methods. Then, the beads are separated from the image background and the beads colors are identified by the characteristics analysis for the RGB color space of the pad image. Finally, the verification is further provided by computer simulation and the beads pad reconstruction, and the results show that this proposed method can identify the number and the colors for the beads in pad image accurately.

Abstract: The cast shadows on the background of the object will distinctly affect the recognition of the foreground objects. Due to the limitation of shadow removal methods utilizing texture, a novel algorithm based on Gaussian Mixture Model (GMM) and HSV color space is proposed. Firstly, moving regions are detected using GMM. Secondly, we make two pre-classifiers accurate and adaptive to the change of shadow by using the features of shadow in RGB and HSV color space. Experimental results show that the proposed method is efficient and robust.

Abstract: This paper introduces a novel implementation of in-vehicle traffic signs and traffic lights recognition system based on FPGA multi-core processers. Images could be processed with multi-core parallel processor using the corresponding relationships of traffic signs’ color and shape. We implement this vehicle vision system on SOPC hardware platform.

Abstract: The traffic lights identification algorithms is an important part of the platform for automatic driving technology and it is also applied in the remote control system. As the absolute standard of behavior instruction, lights are the most firsthand object to judge. Image recognition technology has been applied in the Gray Spaces and HSI space, but Comparing with RGB color space, the latter is easier to understand and realize. This paper puts forward a kind of identification algorithm for single or multiple lights. According to the target image numerical characteristics in the RGB color space and judging from the target area needed and the related parameters extracted, The feasibility of this algorithm is proved in theory and application and the experimental results are satisfactory in the Matlab environment.

Abstract: Along with digitizing and multimedia era, the image has not changed from the original entity into any changes can be dealt with digital preservation methods. Although the digital image capture technology means more and more developed, but there are still many variables affect the quality of an image. An image quality usually depends on the user's usage or changes in the natural environment. Due to the natural environment of the most common factors that influence is light, so an image of the brightness distribution over the target object caused by extreme hardly recognizable condition common. Therefore, we will use the independent component analysis of an input color images Red, Green, and Blue three Color Space to the main component analysis, in order to achieve the target tracking and analysis.

Abstract: According to the analysis of every feature element’s grey images in RGB color space and HSI color space, each of the elements represents different information of the color image. From the analysis of the Histogram of color images, the value range of hue H basically keeps stable, which is proved by experiments to be the most stable and representative one. Finally we illustrated by application instances that the method of recognition and tracking of the objective moving robot based on hue character H is applicable.