• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.1446-1449
• /
• 2005

The purpose of this study is the real-time shape measurement of three-dimensional object by using color coded information. The paper relates to non-contact optical measurements of surface profiles or displacements, because of optical measurement systems are advantageous over using mechanical sensing, their relatively high speed and non-destructive capabilities. Therefore is particularly useful for three dimensional sensing which requires high horizontal and vertical resolution of measurements over a wide range thereof. Each a red, blue, green by using a inherence colors of hue value are good point.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.727-731
• /
• 2005

We introduce a method of color-coded illumination that is simple and fast. The purpose of this study is the real-time shape measurement of three-dimensional object by using color-coded information. The object is illuminated by a prism color spectrum. A color spectrum of a white-light source is imaged onto the object by illumination from one certain direction. The object is observed by a color CCD camera from a direction of observation, which is different from the direction of illumination. It can be evaluated by the red, blue, green using a inherence colors of hue value are good point.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2007.10a
• /
• pp.293-297
• /
• 2007

This thesis suggests a new algorithm to detects multiple moving objects using a CMODE(Correct Multiple Object DEtection) method in the color images acquired in real-time and to track the interested pedestrian using motion and hue information. The multiple objects are detected, and then shaking trees or moving cars are removed using structural characteristics and shape information of the man , the interested pedestrian can be detected, The first similarity judgment for tracking an interested pedestrian is to use the distance between the previous interested pedestrian's centroid and the present pedestrian's centroid. For the area where the first similarity is detected, three feature points are calculated using k-mean algorithm, and the second similarity is judged and tracked using the average hue value for the $3{\times}3$ area of each feature point. The zooming of camera is adjusted to track an interested pedestrian at a long distance easily and the FOV(Field of View) of camera is adjusted in case the pedestrian is not situated in the fixed range of the screen. As a experiment results, comparing the suggested CMODE method with the labeling method, an average approach rate is one fourth of labeling method, and an average detecting time is faster three times than labeling method. Even in a complex background, such as the areas where trees are shaking or cars are moving, or the area of shadows, interested pedestrian detection is showed a high detection rate of average 96.5%. The tracking of an interested pedestrian is showed high tracking rate of average 95% using the information of situation and hue, and interested pedestrian can be tracked successively through a camera FOV and zooming adjustment.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.7
• /
• pp.1513-1517
• /
• 2005

In this paper, I make use of a Multi-Channel skin color model with Hue, Cb, Cg using Red, Blue, Green channel altogether which remove bight component as being consider the characteristics of skin color to do modeling more effective to a facial skin color for extracting a facial area. 1 used efficient HOLA(Higher order local autocorrelation function) using 26 feature vectors to obtain both feature vectors of a facial area and the edge image extraction using Harr wavelet in image which split a facial area. Calculated feature vectors are used of date for the facial recognition through learning of neural network It demonstrate improvement in both the recognition rate and speed by proposed algorithm through simulation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.8
• /
• pp.1653-1662
• /
• 2012

Recently, Organic Light Emitting Diode (OLED) that is broadly applied as next generation display has various advantages. However, OLED display causes unbalanced color tone due to the difference of luminance efficiency among luminous elements. In this paper, we propose adaptive color shifter (ACS) to resolve the RGB channel unbalance and to have wide color range of a relatively weak channel using the image processing method. proposed ACS system was simulated using a variety of image. Also, we numerically analyzed using hue histogram, CIE-1931 xyz color space.

• Journal of Animal Environmental Science
• /
• v.7 no.3
• /
• pp.177-182
• /
• 2001

This study was conducted to find out the coefficient relationships between intensity values image processing and pollution density of slurries. Slurry images were obtained from the image processing system using personnel computer and CCD-camera. Software, written in Visual $c^{++}$, combined the functions of the image capture, image processing and image analysis. The data of image processing for slurries were analyzed by the method of regression analysis. The results are as follows. 1. Red(R)-values among image processing data were obtained the highest correlation coefficient 0.9213 for detecting COD. Also, green(G)-value were obtained the highest correlation coefficient 0.9019 fur detecting BOD. Blue(B)-value could not find significant values to detect the pollution resources density. 2. Hue(H)-values among image processing data were obtained the highest correlation coefficient 0.9466 for detecting BOD. This fact could be used in detecting BOD 3. Green(G)-value, GRAY-value, Hue(H)-value, Saturation(5)-value and Intensity(I)-value were the correlation coefficient more than 0.8 for BOD. Hue(H)-value was higher correlation coefficient than any other value. It was possible to detect pollution density of slurries by using the image processing system. 4. Red(R)-value, GRAY-value and Saturation(5)-value were obtained the correlation coefficient more than 0.8 for detecting COD. a-value had the highest correlation coefficient Among these values. It was possible to detect density indirectly by using the image processing system. 5. SS-density were obtained the correlation coefficient less than 0.8 by using the image processing system. The density of $NH_4$-N and $NO_3$-N were obtained correlation coefficient less than 0.2.

• The KIPS Transactions:PartB
• /
• v.17B no.2
• /
• pp.169-176
• /
• 2010

This paper proposes color transformation of images based on user's preference. Traditional color transformation method transforms only hue based on existing templates that define range of harmonious hue. It does not change saturation and intensity. Users would appreciate the resulting images that adjusted unnatural hue of images. Since color is closely related to peoples' emotion, we can enhance interaction of emotion-based contents and technologies. Therefore, in this paper, we define the range of color of each emotion for the transformation of color and perform the transformation of hue, saturation and intensity. However, the relationship of color and emotion depends on the culture and environment. To reflect these characteristics in color transformation, we propose the transformation of color that is based on user's preference and as a result, people would be more satisfied. We adopt interactive genetic algorithm to learn about user's preference. We surveyed the subject to analyze user's satisfaction about transformed images that are based on preference, and we found that people prefer transformed images to original images. Therefore, we conclude that people are more satisfied with the transformation of the templates which reflected user's preference than the one that did not.

• Journal of Korea Society of Industrial Information Systems
• /
• v.17 no.4
• /
• pp.51-59
• /
• 2012

Recently, the study about object tracking using image processing has been active in the field of security and surveillance. Existing security and surveillance systems using multiple cameras have been operating independently. Thus, the chase was difficult when the tracking object move to other monitored areas. In this paper, we propose the way to change the control of camera automatically following the moving direction of objects in multiple cameras. The proposed method detects the object and tracks the object using color information and direction information of object. The color information obtains using the hue and the direction information obtains using the optical flow. At this time, the optical flow is detected for the entire image area of an object that is not applied only to reduce the computational complexity makes it possible to track in real time. In addition, it can be solved to inconvenience of security surveillance system to use existing camera by tracking an object automatically.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.30-36
• /
• 2008

The multimedia that is characterized by multi-media, multi-features, multi-representations, huge volume, and varieties, is rapidly spreading out due to the increasing of application domains. Thus, it is urgently needed to develop a multimedia information system that can retrieve the needed information rapidly and accurately from the huge amount of multimedia data. For the content-based retrieval of moving picture, picture information is generally used. It is generally used when video is segmented. Through that, it can be a structural video browsing. The tasking that divides video to shot is called video segmentation, and detecting the cut for video segmentation is called cut detection. The goal of this paper is to divide moving picture using HMMD(Hue-Mar-Min-Diff) color model and edge histogram descriptor among the MPEG-7 visual descriptors. HMMD color model is more familiar to human's perception than the other color spaces. Finally, the proposed retrieval system is implemented as hardware.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.5
• /
• pp.1004-1012
• /
• 2007

In this paper, we proposed a new car license plate recognition method using an unsupervised ART2 algorithm with HSI color model. The proposed method consists of two main modules; extracting plate area from a vehicle image and recognizing the characters in the plate after that. To extract plate area, hue(H) component of HSI color model is used, and the sub-area containing characters is acquired using modified fuzzy binarization method. Each character is further divided by a 4-directional edge tracking algorithm. To recognize the separated characters, noise-robust ART2 algorithm is employed. When the proposed algorithm is applied to recognize license plate characters, the extraction rate is better than that of existing RGB model and the overall recognition rate is about 97.4%.