Papers by Keyword: HSI Color Space

Abstract: Crop segmentation from outdoor images is still an open problem. In this paper, we proposed a novel crop segmentation method using Gaussian Mixture Model (GMM), which is robust and not sensitive to the challenging outdoor light conditions and complex environmental elements. The method mainly consists of two stages, supervised learning stage and segmentation stage. The GMM is utilized in the former stage to establish crop color model in the HSI color space and a decision function is provided in the latter stage to realize the final crop segmentation. Comparing experimental results show that our method outperforms the other commonly used methods in yielding the highest performance of 94.91% with the lowest standard deviation of 3.14%.

Abstract: Tobacco is widely planted worldwide as an important economic crop. The differences of planting environment and growth status in different regions lead to different levels of tobacco quality, while color is one of the important indexes to evaluate the quality grade of tobacco leaves. Even for those that are planted in the same area, colors of different grades of tobacco leaves vary greatly, so the color of tobacco leaves is often used as the main evaluating index in tobacco leaves grading. In this paper color extraction of standard tobacco leaves based on HSI color space was thoroughly studied. H, S and I component would be quantified and extracted by using color histogram, then the average value corresponding to every color component was calculated. After extraction and calculation on the same level of standard tobacco leaves, the ranges of three color components could be obtained in HSI color space by using statistical method, and provide data information for tobacco leaves grading.

Abstract: We designed a color recognition algorithm based on HSI color space, through front-facing camera to identify the scene in front of the robot, then video stream was cut into frames and image processing was conducted. The presented algorithm does well on the robot experiment platform, we can carry out the color recognition, and also can identify the size of the red area through the parameter setting, so as to choose the preset area for tracking. Simulation results show that the optimization function has successfully filtered distractors, the system basically meets the requirements of real-time, providing effective support for the robot tracking.

Abstract: During deep penetration laser welding, changes in the metal vapor plume contain information about the stability of welding process. A high-speed camera was used to online monitor the welding process in order to detect the laser welding defects. A color segmentation clustering algorithm based on HSI color space was proposed for processing the recorded welding sequences. The effectiveness of algorithms based on different model is discussed, welding experimental results showed that the proposed algorithm could achieve better image segmentation, and it highlighted the edge of the metal vapor details in the image.

Abstract: In this paper, we put forward an improved non-photorealistic rendering method for generating a colored pencil drawing from digital image. First, to make sure the result can retain the original color information, we use the original pixel value instead of the black dot which generated by the traditional white-noise generating method. Second, we added a ratio for the Kirsch operator to be suitable for different images with different details. Third, we present a new approach which extruded form the luminance of the original image to determine the stroke orientation. Based on our methods, the quality of traditional pencil illustration can be guaranteed to a certain extent, and an effective and convenient tool is provided to generate the same drawings in style with artists and illustrations even for the users that have not been trained professionally.

Abstract: Extraction of feather defects is difficult because of their complicated and diversified characteristics. It is proposed that feather stain defects be extracted in HSI color space according to color characters of different types of feather defects. The improved variational level set method is adopted to locate and segment the feather stains on that basis. Experiment results show that the proposed methods can extract feather stains effectively and segment them accurately.

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.

Abstract: Quantitative evaluation of repairing effect of bone grafting material is one of the essential studying subjects. However, traditional evaluation methods are subjective and qualitative. In this paper, the region of new bone from a bone repairing biomaterial planted image is extracted based on color image segmentation and then statistically analyzed to evaluate the property of bone grafting material quantitatively. HSI color model, which corresponds with people’s vision system for color is used to achieve ideal segmental results and effective utilization of color information. The S and I variable are used as thresholding condition for image segmentation, thereby obtaining the area of new bone. The effect of BMP contained in BMP/α-TCP is estimated furthermore. Experimental results show that the composite BMP/α-TCP induce more bone than pure α-TCP in virtue of BMP. This study provides theoretical and experimental suggestions for clinical applications of BMP/α-TCP.