• International conference on construction engineering and project management
• /
• 2020.12a
• /
• pp.313-322
• /
• 2020

The recognition of the risk hazards is a vital step to effectively prevent accidents on a construction site. The advanced development in computer vision systems and the availability of the large visual database related to construction site made it possible to take quick action in the event of human error and disaster situations that may occur during management supervision. Therefore, it is necessary to analyze the risk factors that need to be managed at the construction site and review appropriate and effective technical methods for each risk factor. This research focuses on analyzing Occupational Safety and Health Agency (OSHA) related to risk zone identification rules that can be adopted by the image recognition technology and classify their risk factors depending on the effective technical method. Therefore, this research developed a pattern-oriented classification of OSHA rules that can employ a large scale of safety hazard recognition. This research uses joint reasoning of risk zone Identification and numeric input by utilizing a stereo camera integrated with an image detection algorithm such as (YOLOv3) and Pyramid Stereo Matching Network (PSMNet). The research result identifies risk zones and raises alarm if a target object enters this zone. It also determines numerical information of a target, which recognizes the length, spacing, and angle of the target. Applying image detection joint logic algorithms might leverage the speed and accuracy of hazard detection due to merging more than one factor to prevent accidents in the job site.

• Journal of Internet Computing and Services
• /
• v.18 no.1
• /
• pp.51-55
• /
• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Progress in Medical Physics
• /
• v.24 no.3
• /
• pp.191-197
• /
• 2013

Upon radiation treatment, it is the important factor to monitor the patient's motion during radiation irradiated, since it can determine whether the treatment is successful. Thus, we have developed the system in which the patient's motion is monitored in real time and moving treatment position can be automatically corrected during radiation irradiation. We have developed the patient's position monitoring system in which the patient's position is three dimensionally identified by using two CCD cameras which are orthogonal located around the isocenter. This system uses the image pattern matching technique using a normalized cross-correlation method. We have developed the system in which trigger signal for beam on and off is generated by quantitatively analyzing the changes in a treatment position through delivery of the images taken from CCD cameras to the computer and the motor of moving couch can be controlled. This system was able to automatically correct a patient's position with the resolution of 0.5 mm or less.

• Journal of Biomedical Engineering Research
• /
• v.25 no.5
• /
• pp.329-334
• /
• 2004

The electronic nose (E-nose) recently finds its applications in medical diagnosis, specifically on detection of diabetes, pulmonary or gastrointestinal problem, or infections by examining odors in the breath or tissues with its odor characterizing ability. The odor recognition performance of E-nose can be improved by manipulating the sensor array responses of vapors in time-profile forms. The different chemical interactions between the sensor materials and the volatile organic compounds (VOC's) leave unique marks in the signal profiles giving more information than collection of the conventional piecemal features, i.e., maximum sensitivity, signal slopes, rising time. In this study, to use them in vapor recognition task conveniently, a novel time-profile method was proposed, which is adopted from digital image pattern matching. The degrees of matching between 8 different vapors were evaluated by using the proposed method. The test vapors are measured by the silicon-based gas sensor array with 16 CB-polymer composites installed in membrane structure. The results by the proposed method showed clear discrimination of vapor species than by the conventional method.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.42 no.6
• /
• pp.133-140
• /
• 2005

This paper presents a rapid face shape acquisition system. The system is composed of two cameras and one projector. The technique works by projecting a pattern on the object and capturing two images with two cameras. We use a 'one shot' system which provides 3D data acquired by single image per camera. The system is good for rapid data acquisition as our purpose. We use the 'absolutely coded pattern' using the hue and saturation of pattern lines. In this 'absolutely coded pattern' all patterns have absolute identification numbers. We solve the correspondence problem between the two images by using epipolar geometry and absolute identification numbers. In comparison to the 'relatively coded pattern' which uses relative identification numbers, the 'absolutely coded pattern' helps obtain rapid 3D data by one to one point matching on an epipolar line. Because we use two cameras, we obtain two images which have similar hue and saturation. This enables us to have the same absolute identification numbers in both images, and we can use the absolutely coded pattern for solving the correspondence problem. The proposed technique is applied to face data and the total time for shape acquisition is estimated.

• Korean Journal of Cognitive Science
• /
• v.12 no.4
• /
• pp.49-56
• /
• 2001

When multiple features are presented in the image the computational models for stereopsis select the most activated matches through the excitatory and inhibitory interactions among all possible matches. Using the random-dot stereogram with two surfaces. we investigate whether human binocular mechanism selects the most activated matches. The dots consisting a surface lying in a fixation plane were selected randomly while each of the dots consisting the other surface was paired with each of the original dots in the following manner. After finding the position of each dots in the original random pattern we placed an additional dot to the left and to the right of the original position in each of the left and right image of a stereogram respectively. The luminance of additional dots was varied while that of the original random dots was fixed so that the hypothetical matches presumably could be activated differently. Across the luminance condition the depth of each surface was measured to examine whether matches to be selected were changed depending on the activation level of possible matches. When the luminance of two patterns was within 30% of one another observers perceived an opaque surface. Beyond this value two transparent surfaces were seen with the magnitude of perceived depth varying with relative luminance of two patterns. When original pattern was brighter one additional surface was perceived at the depth corresponding to the disparity of original pattern. When original dot was dimmer. however the depth of an additional surface corresponded to the disparity of newly introduced pattern. These results suggest that there are dynamic interactions within the matching process whereby highly activated matches inhibit weaker one.

• Journal of Broadcast Engineering
• /
• v.19 no.3
• /
• pp.396-404
• /
• 2014

The field of searching clothing, which is very difficult due to the nature of the informal sector, has been in an effort to reduce the recognition error and computational complexity. However, there is no concrete examples of the whole progress of learning and recognizing for cloth, and the related technologies are still showing many limitations. In this paper, the whole process including identifying both the person and cloth in an image and analyzing both its color and texture pattern is specifically shown for classification. Especially, deformable search descriptor, LBPROT_35 is proposed for identifying the pattern of clothing. The proposed method is scale and rotation invariant, so we can obtain even higher detection rate even though the scale and angle of the image changes. In addition, the color classifier with the color space quantization is proposed not to loose color similarity. In simulation, we build database by training a total of 810 images from the clothing images on the internet, and test some of them. As a result, the proposed method shows a good performance as it has 94.4% matching rate while the former Dense-SIFT method has 63.9%.

• Journal of KIISE:Databases
• /
• v.32 no.5
• /
• pp.498-508
• /
• 2005

A shape data is used one oi most important feature for image retrieval as data to reflect meaning of image. Especially, structural feature of shape is widely studied because it represents primitive properties of shape and relation information between basic units well. However, most structural features of shape have the problem that it is not able to guarantee an efficient search time because the features are expressed as graph or tree. In order to solve this problem, we generate curvature-based morphological graph, End design key to cluster shapes from this graph. Proposed this graph have contour features and morphological features of a shape. Shape retrieval is accomplished by stages. We reduce a search space through clustering, and determine total similarity value through pattern matching of external curvature. Various experiments show that our approach reduces computational complexity and retrieval cost.

• Journal of the Korean Society of Fisheries and Ocean Technology
• /
• v.48 no.4
• /
• pp.469-478
• /
• 2012

To manage, sort, and grade fishery resources, it is necessary to measure their morphometric characteristics. This labor-intensive task involves performing repetitive operations on land and on a research vessel. To reduce the amount of labor required, a vision-based automatic measurement system (VAMS) for the measurement of morphometric characteristics of flatfish, such as total length (TL), body width (BW), and body height (BH), has been developed as part of a database management system for fishery resources management. This system can also measure the mass (M) of flatfish. In the present study, we describe a morphological image processing algorithm for the measurement of certain characteristics of flatfish. This algorithm, which involves preprocessing, edge pattern matching, and edge point detection, is effective in cases where the flatfish being measured has a deformed tail and is randomly oriented. The satisfactory performance of the proposed algorithm is also demonstrated by means of experiments involving the measurement of the BW, TL and BH of a flatfish when it is straightened (BW : 117mm, TL : 329mm, BH : 24.5mm), when its tail is deformed, and when it is randomly oriented.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.16 no.1
• /
• pp.46-56
• /
• 1991

In this paper, 16word X 8bit Content Addressable and Reentrant Memory(CARM) is described. This device has 4 operation modes(read, write, match, reentrant). The read and write operation of CARM is like that of static RAM, CARM has the reentrant mode operation where the on chip garbage collection is accomplished conditionally. Thus function can be used for high speed matching unit of dynamic data flow computer. And CARM also can encode matching address sequentially according to therir priority. CARM consists of 8 blocks(CAM cell, Sequential Address Encoder(S.A.E). Reentrant operation. Read/Write control circuit, Data/Mask Register, Sense Amplifier, Encoder. Decoder). Designed DARM can be used in data flow computer, pattern, inspection, table look-up, image processing. The simulation is performed using the QUICKSIM logic simulator and Pspice circuit simulator. Having hierarchical structure, the layout was done using the 3{\;}\mu\textrm{m} n well CMOS technology of the ETRI design rule.