• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.10
• /
• pp.839-846
• /
• 2016

Bin picking is a task of picking a small object from a bin. For accurate bin picking, the 3D pose information, position, and orientation of a small object is required because the object is mixed with other objects of the same type in the bin. Using this 3D pose information, a robotic gripper can pick an object using exact distance and orientation measurements. In this paper, we propose a 3D vision technique for accurate measurement of 3D position and orientation of small objects, on which a paper label is stuck to the surface. We use a maximally stable extremal regions (MSERs) algorithm to detect the label areas in a left bin image acquired from a stereo camera. In each label area, image features are detected and their correlation with a right image is determined by a stereo vision technique. Then, the 3D position and orientation of the objects are measured accurately using a transformation from the camera coordinate system to the new label coordinate system. For stable measurement during a bin picking task, the pose information is filtered by averaging at fixed time intervals. Our experimental results indicate that the proposed technique yields pose accuracy between 0.4~0.5mm in positional measurements and $0.2-0.6^{\circ}$ in angle measurements.

• Journal of dental hygiene science
• /
• v.20 no.1
• /
• pp.59-66
• /
• 2020

Background: This study aims to analyze the job stress of dental hygienists and the factors affecting somatization and to provide basic data for effectively managing job stress and somatization of dental hygienists. Methods: In this study, the data collected from 208 dental hygienists working in Jeollabuk-do Province were analyzed. Job stress was investigated using a questionnaire with 43 questions. In addition, the degree of somatization was evaluated through a simplified psychotherapy examination (Symptom Check List-90-Revision). Results: Age, employment history, position, average monthly income, night duty execution status, and perceived health status were significantly associated with job stress (p<0.05). The job stress sub-items scores based on general characteristics showed significance in 'workload' for those working a five-day workweek and perceived health status (p<0.05). Age, average monthly income, and perceived health status were noted in 'role conflict as a professional'. In 'lack of expertise and skill', it was noted that age, employment history, position, income, and night clinic were implemented. In 'improper treatment and interpersonal issues', level of education and perceived health status were significant (p<0.05). The higher the job stress, the higher the somatization symptom score (p<0.05), and the higher the job stress component, the higher the somatization symptom score (p<0.01). Conclusion: The job stress of dental hygienists should be reduced, and the symptoms of somatization should be mitigated. To improve the quality of medical services and the work efficiency of dental hygienists, proper treatment and compensation systems should be implemented for them to take pride as professional. Further, programs and regulations on mitigating job stress and somatization symptoms should be developed.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.2
• /
• pp.135-141
• /
• 2008

In this paper, we propose colored-hear recognition that distinguishing feature of synesthesia for human sensing by shared vision and specific sense of hearing. We perceived what potential influence of human's structured object recognition by visual analysis through the camera, So we've studied how to make blind persons can feel similar vision of real object. First of all, object boundaries are detected in the image data representing a specific scene. Then, four specific features such as object location in the image focus, feeling of average color, distance information of each object, and object area are extracted from picture. Finally, mapping these features to the audition factors. The audition factors are used to recognize vision for blind persons. Proposed colored-hear transformation for recognition can get fast and detail perception, and can be transmit information for sense at the same time. Thus, we were get a food result when applied this concepts to blind person's case of image recognition.

• Journal of Internet Computing and Services
• /
• v.20 no.1
• /
• pp.77-86
• /
• 2019

As the number of single-person households increases, it is not easy to ask for help alone if a single-person household is severely injured in the home. This paper detects abnormal event when members of a single household in the home are seriously injured. It proposes an vision detection algorithm that analyzes and recognizes patterns through videos that are collected based on home CCTV. And proposes audio detection algorithms that analyze and recognize patterns of sound that occur in households based on Smartphones. If only each algorithm is used, shortcomings exist and it is difficult to detect situations such as serious injuries in a wide area. So I propose a fusion method that effectively combines the two algorithms. The performance of the detection algorithm and the precise detection performance of the proposed fusion method were evaluated, respectively.

• Journal of dental hygiene science
• /
• v.19 no.2
• /
• pp.113-121
• /
• 2019

Background: We investigated somatization symptoms experienced by dental hygienists due to stress from emotional labor. Our aim was to provide basic research data that could be useful in the development of efficient stress management schemes for this occupational group. Methods: We analyzed data collected from 208 dental hygienists working in Jeollabuk-do Province, Korea. To measure the level and intensity of emotional labor among research participants, we used the Korean Emotional Labor Questionnaire. We used the Somatization Symptom Checklist-90-Revised (SCL-90-R) to measure the level of somatization symptoms among participants. Results: On analyzing the level of emotional labor and somatization symptoms according to general characteristics, participants aged 23~25 years showed high scores for stress due to emotional labor (p<0.05). Working 5 days per week, subjective health status, and organizational support and protection systems were found to correlate with the level of stress due to emotional labor (p<0.05). In the analysis of correlations between emotional labor and somatization symptoms, scoring high across all domains of emotional labor was associated with scoring high for somatization symptoms in the subdomains of emotional labor. When emotional labor and demographical variables were used as independent variables, having higher scores for emotional labor and having poor subjective health status were found to be associated with having higher levels of somatization symptoms (p<0.05). Conclusion: Our results showed that working at night and organizational support and protection systems were correlated with emotional labor and somatization symptoms. Measures must be taken at the organizational level to reduce emotional labor and somatization symptoms.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.1
• /
• pp.77-84
• /
• 2024

In this paper, we propose a method for accurately and rapidly detecting defects in wire harnesses by utilizing computer vision to calculate six crucial measurement values: the length of crimped terminals, the dimensions (width) of terminal ends, and the width of crimped sections (wire and core portions). We employ Harris corner detection to locate object positions from two types of data. Additionally, we generate reference points for extracting measurement values by utilizing features specific to each measurement area and exploiting the contrast in shading between the background and objects, thus reflecting the slope of each sample. Subsequently, we introduce a method using the Euclidean distance and correction coefficients to predict values, allowing for the prediction of measurements regardless of changes in the wire's position. We achieve high accuracy for each measurement type, 99.1%, 98.7%, 92.6%, 92.5%, 99.9%, and 99.7%, achieving outstanding overall average accuracy of 97% across all measurements. This inspection method not only addresses the limitations of conventional visual inspections but also yields excellent results with a small amount of data. Moreover, relying solely on image processing, it is expected to be more cost-effective and applicable with less data compared to deep learning methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.311-326
• /
• 2024

The rapid development of neural network technology promotes the neural network model driven by big data to overcome the texture effect of complex objects. Due to the limitations in complex scenes, it is necessary to establish custom template matching and apply it to the research of many fields of computational vision technology. The dependence on high-quality small label sample database data is not very strong, and the machine learning system of deep feature connection to complete the task of texture effect inference and speculation is relatively poor. The style transfer algorithm based on neural network collects and preserves the data of patterns, extracts and modernizes their features. Through the algorithm model, it is easier to present the texture color of patterns and display them digitally. In this paper, according to the texture effect reasoning of custom template matching, the 3D visualization of the target is transformed into a 3D model. The high similarity between the scene to be inferred and the user-defined template is calculated by the user-defined template of the multi-dimensional external feature label. The convolutional neural network is adopted to optimize the external area of the object to improve the sampling quality and computational performance of the sample pyramid structure. The results indicate that the proposed algorithm can accurately capture the significant target, achieve more ablation noise, and improve the visualization results. The proposed deep convolutional neural network optimization algorithm has good rapidity, data accuracy and robustness. The proposed algorithm can adapt to the calculation of more task scenes, display the redundant vision-related information of image conversion, enhance the powerful computing power, and further improve the computational efficiency and accuracy of convolutional networks, which has a high research significance for the study of image information conversion.

• Design & Manufacturing
• /
• v.18 no.3
• /
• pp.1-8
• /
• 2024

Macular degeneration is a disease that damages the macula, the center of the retina, and is one of the three major eye diseases along with glaucoma and diabetic retinopathy. The optic nerve and most of the photoreceptor cells are located here, and since this is where images of objects are formed, it is the most important area for vision. The main symptom of macular degeneration is the inability to clearly distinguish the shape of objects or the inability to distinguish colors and light and dark. It is also a serious eye disease that causes black spots in the center of the field of vision. However, it is difficult to distinguish it from the form of vision loss due to presbyopia, so early diagnosis is often missed. The most common treatment for macular degeneration is antibody injection therapy. This treatment requires regular injections once every 1-2 months. When receiving antibody injection therapy, the fear of having to inject directly into the eye and the cost of long-term repeated procedures are a great burden to patients. To overcome these problems, special sustained-release formulations using drug delivery systems are being developed. Since the release speed and release time of the drug can be controlled, the number of times the drug is administered can be drastically reduced. However, the implant (Ø 0.46×6.0mm), which is a sustained-release agent, is manufactured by mixing biodegradable resin (PLGA) and therapeutic agent in a ratio of 4:6, so it is very brittle and there is a high risk of implant damage during handling. In order to safely insert the implant into the eye, a transport device that can be driven with controlled force is required. Therefore, in this study, the lever operating force was measured and analyzed to determine the influence of factors according to the cross-sectional thickness and shape of the linkage produced through injection molding as well as the post-process.

• The Journal of the Korea Contents Association
• /
• v.10 no.7
• /
• pp.107-114
• /
• 2010

Color is a sense signal for human to perceive being through light, and the color is divided into chromatic color and achromatic color. Chromatic color has hue, intensity, and saturation, but achromatic color has only intensity among the properties of chromatic color and doesn't have hue and saturation. Therefore it is important to split colors of image into area for human to perceive colors and not to perceive ones based on vision of human being. In this paper, we find a function to split colors of image into chromatic region of chromatic color region and achromatic region of achromatic color region. First, the input image of RGB color space is converted into the image of HSI color space in consideration of human vision and get a binary image from the converted image. After then, a function to split colors into ROC(ROC: Region of chromatic.) and ROA(ROA:Region of achromatic) is yield. It is difficult to split color of a general image into ROC and ROA. Therefore, to get the chromatic area and achromatic area, we make gradient images to have all range of intensity and range of saturation and to have a little range of hue and yield the function. The evaluation is tested using subjective-quality by 50 non-experts for result images of test images and general images. The results of the proposed method get better 27.5~32.96% than these of the conventional method

• The Korean Journal of Vision Science
• /
• v.20 no.4
• /
• pp.413-420
• /
• 2018

Purpose : We present a novel method for the analysis of blue light applied by the analysis method of David L. with optical experiment and blue light by measuring the transmittance by dividing it by the refractive power in the spectacle lens made by MR8. Methods : The lenses of -8.00D, -7.00D, -6.00D, -5.00D, -4.00D, -3.00D, and 0.00D manufactured by MR8 being sold in the market, were selected. The transmittance was measured at the intervals of 5 nm from 200 to 1000 nm with UV-VIS Spectrophotometers (SolidSpec 3700), and they were in range of the blue light (380 to 500 nm) analyzed by a David L.'s analysis method. Results : All of the MR8 lenses selected for this study almost completely blocked at the UV range. A lens of -8.00D was measured as the lowest transmittance of 59.56% in the blue light area and low values were measured at the blue areas 1 and 2 according to the analysis of David L.In the infrared ray area, the transmittance of all lenses gradually decreased. The average value of the luminous transmittance was 23.67% ~ 26.33% and then gradually decreased from -4.00D. Conclusion : Applying the analysis of David L., a minimum of 41.28% and a maximum of 46.60% were measured at the blue light 1 area and a minimum of 87.30% and a maximum of 97.55% were measured at the blue light 2 area. A minimum of 86.83% and a maximum of 96.55% were measured at the blue light 3 area, and the average was 94%. The luminous transmittance of the -3.00D lens was 26.33%, which was the highest, and that -8.00D was 23.67%, which was the lowest.