• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.48 no.3
• /
• pp.90-98
• /
• 2011

The recognition and classification of paddy rice disease are of major importance to the technical and economical aspect of agricultural industry over the world. Computer vision techniques are used to diagnose rice diseases and to efficiently manage crops. Segmentation of lesions is the most important technique to detect paddy rice disease early and accurately. A new Gaussian Mean (GM) method was proposed to segment paddy rice diseases in various color spaces. Different color spaces produced different results in segmenting paddy diseases. Thus, this empirical study was conducted with the motivation to determine which color space is best for segmentation of rice disease. It included five color spaces; NTSC, CIE, YCbCr, HSV and the normalized RGB(NRGB). The results showed that YCbCr was the best color space for optimal segmentation of the disease lesions with 98.0% of accuracy. Furthermore, the proposed method demonstrated that diseases lesions of paddy rice can be segmented automatically and robustly.

• Journal of Broadcast Engineering
• /
• v.15 no.4
• /
• pp.527-539
• /
• 2010

Most video coding systems use YCbCr color space for their inputs, but RGB space is more preferred in the field of high fidelity video because the compression gain from YCbCr becomes disappeared in the high quality operation region. In order to improve the coding performance of RGB video signal, this paper presents an adaptive frequency-selective weighted prediction algorithm. Based on the sign agreement and the strength of frequency-domain correlation of residual color planes, the proposed scheme adaptively selects the frequency elements as well as the corresponding prediction weights for better utilization of inter-plane correlation of RGB signal. Experimental results showed that the proposed algorithm improves the coding gain of around 13% bitrate reduction, on average, compared to the common mode of 4:4:4 video coding in the state-of-the-art video compression standard, H.264/AVC.

• Journal of the Korea Society of Computer and Information
• /
• v.15 no.5
• /
• pp.57-65
• /
• 2010

In this paper, we propose a new real-time algorithm detecting the flame and smoke in digital CCTV images. Because the forest fire causes the enormous human life and damage of property, the early management according to the early sensing is very important. The proposed algorithm for monitoring forest fire is classified into the flame sensing and detection of smoke. The flame sensing algorithm detects a flame through the conditional test at YCbCr color model from the single frame. For the detection of smoke, firstly the background range is set by using differences between current picture and the average picture among the adjacent frames in the weighted value, and the pixels which get out of this range and have a gray-scale are detected in the smoke area. Because the proposed flame sensing algorithm is stronger than the existing algorithms in the change of the illuminance according to the quantity of sunshine, and the smoke detection algorithm senses the pixel of a gray-scale with the smoke considering the amount of change for unit time, the effective early forest fire detection is possible. The experimental results indicate that the proposed algorithm provides better performance than existing algorithms.

• The Journal of the Korea Contents Association
• /
• v.8 no.2
• /
• pp.74-82
• /
• 2008

This paper investigates chrominance reconstruction methods that reconstruct subsampled chrominance information efficiently using the correlation between luminance and chrominance components in the decompression process of compressed images, and analyzes drawbacks involved in the adaptive-weighted 2-dimensional linear interpolation among the methods, which shows higher efficiency in the view of computational complexity than other methods. To improve the drawback that the spatial frequency distribution is not considered for the decompressed image and to support the application on a low-performance system in behalf of 2-dimensional linear interpolation, this paper proposes the multi-mode reconstruction method which uses three reconstruction methods having different computational complexity from each other according to the degree of edge response of luminance component. The performance evaluation on a development platform for embedded systems showed that the proposed reconstruction method supports the similar level of image quality for decompressed images while reducing the overall computation time for chrominance reconstruction in comparison with the 2-dimensional linear interpolation.

• Journal of Korea Multimedia Society
• /
• v.4 no.1
• /
• pp.67-74
• /
• 2001

In this paper, we propose a face detection algorithm using the color and shape information in color still images. The proposed algorithm is only applied to chrominance components(Cb and Cr) in order to reduce the variations of lighting condition in YCbCr color space. Input image is segmented by pixels with skin-tone color and then the segmented mage follows the morphological filtering an geometric correction to eliminate noise and simplify the segmented regions in facial candidate regions. Multiple facial regions in input images can be isolated by connected component labeling. Moreover tilting facial regions can be detected by extraction of second moment-based ellipse features.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.6B
• /
• pp.1012-1020
• /
• 2000

In this paper, This paper presents a new algorithm which is used for detecting and extracting human masks from a color still image. The regions where each pixel has a value of skin-color were extracted from the Cb and Cr images, after the tone of the color image is converted to YCbCr from. A morphological filter is used to eliminate noise in the resulting image. By scanning it in horizontal and vertical ways under ways under threshold value, first candidate section is chosen. If it is not a face, secondary candidate section is taken and is divided into two candidate sections. The proposed algorithm is not affected by the variation of illuminations, because it uses only Cb and Cr components in YCbCr color format. Moreover, the face recognition was possible regardless of the degree of shifting face, changed shape, various sizes of the face, and the quality of image.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.2
• /
• pp.57-63
• /
• 2015

Compared to other emotion recognition technology, facial expression recognition technology has the merit of non-contact, non-enforceable and convenience. In order to apply to a psychological robot, vision technology must be able to quickly and accurately extract the face region in the previous step of facial expression recognition. In this paper, we remove the background from any image using the YCbCr skin color technology, and use Haar-like Feature technology for robust face detection. We got the result of improved processing speed and robust face detection by removing the background from the input image.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.24 no.2
• /
• pp.214-224
• /
• 2016

This paper proposes an algorithm to effectively detect the traffic lights and recognize the traffic signals using a monocular camera mounted on the front windshield glass of a vehicle in day time. The algorithm consists of three main parts. The first part is to generate the candidates of a traffic light. After conversion of RGB color model into HSI and YCbCr color spaces, the regions considered as a traffic light are detected. For these regions, edge processing is applied to extract the borders of the traffic light. The second part is to divide the candidates into traffic lights and non-traffic lights using Haar-like features and Adaboost algorithm. The third part is to recognize the signals of the traffic light using a template matching. Experimental results show that the proposed algorithm successfully detects the traffic lights and recognizes the traffic signals in real time in a variety of environments.

• Journal of Broadcast Engineering
• /
• v.20 no.5
• /
• pp.770-773
• /
• 2015

The contrast of the intensity components of color images usually needs to be improved in order to enhance the visual quality of color images. However, pure color regions can be saturated due to the excessive enhancement of that color. In this paper, a new method for enhancing the visual quality of color images using saturation components in the HSI color space is proposed, and the same enhancement technique in the YCbCr color space is proposed. Computer simulations show that the proposed method provides improved visual quality compared to the conventional methods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.594-597
• /
• 2010

This paper proposes a fire detection algorithm using low-cost camera to detect visual features of fire. In the previous work sensor cameras were used, but here we use very simple cameras. This method uses YCbCr and YIQ color model to detect candidate regions of fire. The candidate areas are extracted from the boundaries of the fire. noise removal elimination is performed. Regardless of environmental changes around the fire area, the results of the proposed algorithm are very satisfactory.