• The Journal of the Korea Contents Association
• /
• v.8 no.11
• /
• pp.85-93
• /
• 2008

For music score recognition, several approaches have been proposed including shape matching, statistical methods, neural network based methods and structural methods. In this paper, we deal with recognition for low resolution images which are captured by the digital camera of a mobile phone. Considerable distortions are included in these low resolution images, so when existing technology is used, many problems appear. First, captured images are not stable in the sense that they contain lots of distortions or non-uniform illumination changes. Therefore, notes or symbols in the music score are damaged and recognition process gets difficult. This paper presents recognition technology to overcome these problems. First, musical note to head, stick, tail part are separated. Then template matching on head part of musical note, and remainder part is applied. Experimental results show nearly 100% recognition rate for music scores with single musical notes.

• Journal of Broadcast Engineering
• /
• v.19 no.1
• /
• pp.56-63
• /
• 2014

This paper deals with a binarization for plate number recognition. The binarization process converts an image into a binary image and plays an important role for automatically recognizing plate number. The rear license plate has often a shadowed image which causes erroneous binarized image due to non-uniform illumination. In this paper, a binarization method is proposed in which the shadow line is detected in a rear plate with a shadow. And then the histogram matching is conducted for the two image separated by the shadow line. After histogram matching, two images are joined and finally Otsu method is applied for the binarization. In the experiment, the proposed algorithm shows robust performance compared to the conventional method in the presence of estimation error in the shadow line.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.12
• /
• pp.5990-6008
• /
• 2019

Recognizing license plate from its traffic camera captured images is one of the most important aspects in many traffic management systems. Despite many sophisticated license plate recognition related algorithms available online, license plate recognition is still a hot research issue because license plates in each country all round the world lack of uniform format and their camera captured images are often affected by multiple adverse factors, such as low resolution, poor illumination effects, installation problem etc. A novel method is proposed in this paper to solve the inclination problem of license plates in their camera captured images through four parts: Firstly, special edge pixels of license plate are chosen to represent main information of license plates. Secondly, least square methods are used to compute the inclined angle of license plates. Then, coordinate rotation methods are used to rotate the license plate. At last, bilinear interpolation methods are used to improve the performance of license plate rotation. Several experimental results demonstrated that our proposed method can solve the inclination problem about license plate in visual aspect and can improve the recognition rate when used as the image preprocessing method.

• Journal of Information Processing Systems
• /
• v.13 no.5
• /
• pp.1372-1381
• /
• 2017

In this paper, a texture feature extraction method using local energy and local correlation of Gabor transformed images is proposed and applied to an image retrieval system. The Gabor wavelet is known to be similar to the response of the human visual system. The outputs of the Gabor transformation are robust to variants of object size and illumination. Due to such advantages, it has been actively studied in various fields such as image retrieval, classification, analysis, etc. In this paper, in order to fully exploit the superior aspects of Gabor wavelet, local energy and local correlation features are extracted from Gabor transformed images and then applied to an image retrieval system. Some experiments are conducted to compare the performance of the proposed method with those of the conventional Gabor method and the popular rotation-invariant uniform local binary pattern (RULBP) method in terms of precision vs recall. The Mahalanobis distance is used to measure the similarity between a query image and a database (DB) image. Experimental results for Corel DB and VisTex DB show that the proposed method is superior to the conventional Gabor method. The proposed method also yields precision and recall 6.58% and 3.66% higher on average in Corel DB, respectively, and 4.87% and 3.37% higher on average in VisTex DB, respectively, than the popular RULBP method.

• Journal of the Korean Solar Energy Society
• /
• v.31 no.4
• /
• pp.136-141
• /
• 2011

The lightshelf system reduces intense illumination levels of indoor from direct sun light and reflect to lead diffused light into indoor deeply. This study aims to design acurved-lightshelf by a ray tracing method and evaluate the daylighting performance of window integrated with the curved-lightshelf by computer simulations. For this purpose, evaluation test model was designed for the experiments to validate the simulation model, and the curved-lightshelf was designed by the ray tracing method using Ecotect. After the office model was designed using 3D simulation, the average indoor illuminance, luminance and distribution of illuminance were evaluated by simulation which has a algorithm of Radiosity and Ray-Tracing method under four different cases(case1;no lightshelf, case2; Flat board, case3; tilted at $30^{\circ}$ angle, case4; the curved-lightshelf). As results, it turns out that case1 showed higher average illuminance and case4 was more uniformly distributed than case2 and case3, In addition average luminance of case1 was also lower. indicating that the curved-lightshelf would reduce the possibility of the glare, while maintaining the sufficient daylight level.

• Korean Journal of Optics and Photonics
• /
• v.31 no.6
• /
• pp.334-343
• /
• 2020

In this paper, a study of the design of a lighting optical system to form indirect light was conducted, to reduce the glare caused by the hot spot of the LED. In the case of using an LED for indoor lighting, glare is caused because of the high luminance and non-uniform luminance distribution. In particular, LED stands are located close to the user's eyes and are used for a long time, so research to reduce glare is essential. Therefore, in this paper an optical system structural study and the design of an LED stand for glare reduction were conducted. Afterward, the luminance analysis and comparison to an existing LED stand product confirmed that the reflective LED stand proposed in this paper had better performance in terms of glare.

• Journal of Appropriate Technology
• /
• v.6 no.2
• /
• pp.226-237
• /
• 2020

As the number of reported COVID-19 cases rises around the world, regions affected by the virus are taking serious measures to contain its spread. Face shields are one of the highest-need personal protective equipment (PPE) during COVID-19 pandemic. Beyond traditional face masks, as known cases of the coronavirus soar, currently there is a significant shortage of face shields around the world. In response, the protective face shields were designed and fabricated with open-source 3D modelling software and 3D printing technology, respectively. Our face shield consisted of two parts only; a reusable 3D printed headband and a visor made of transparent plastic sheet, as barrier. The resulting 3D printed face shields are affordable, lightweight, one-size-fits-most and ready-to-wear with minimal assemblies, and go on easily over glass, goggle and face mask. To ensure being donated to the healthcare professionals without risk infected by any pathogens, the 3D printed face shields were successfully be disinfected with ultraviolet germicidal irradiation (UVGI dosage of 1000 mJ/cm²) and 70% alcohol. For routine disinfection a UVGI chamber was designed and optimized to provide uniform UV-C illumination with an appreciated fluence for complete decontamination. More than 1,000 face shields were produced already and donated to the special hospitals for COVID-19 patients, quarantines, government and medical agencies in Ethiopia as well as in East-African countries. With certainty, our intention goes beyond the hospitals and other first responders, but not limited for all those who have to stay in the service or be in contact with many other people in the time of COVID-19 pandemic.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.275-284
• /
• 2008

With increases in recent security requirements, biometric technology such as fingerprints, faces and iris recognitions have been widely used in many applications including door access control, personal authentication for computers, internet banking, automatic teller machines and border-crossing controls. Finger vein recognition uses the unique patterns of finger veins in order to identify individuals at a high level of accuracy. This paper proposes new device and methods for touchless finger vein recognition. This research presents the following five advantages compared to previous works. First, by using a minimal guiding structure for the finger tip, side and the back of finger, we were able to obtain touchless finger vein images without causing much inconvenience to user. Second, by using a hot mirror, which was slanted at the angle of 45 degrees in front of the camera, we were able to reduce the depth of the capturing device. Consequently, it would be possible to use the device in many applications having size limitations such as mobile phones. Third, we used the holistic texture information of the finger veins based on a LBP (Local Binary Pattern) without needing to extract accurate finger vein regions. By using this method, we were able to reduce the effect of non-uniform illumination including shaded and highly saturated areas. Fourth, we enhanced recognition performance by excluding non-finger vein regions. Fifth, when matching the extracted finger vein code with the enrolled one, by using the bit-shift in both the horizontal and vertical directions, we could reduce the authentic variations caused by the translation and rotation of finger. Experimental results showed that the EER (Equal Error Rate) was 0.07423% and the total processing time was 91.4ms.

• Journal of Korea Multimedia Society
• /
• v.13 no.9
• /
• pp.1337-1347
• /
• 2010

Fingerprint recognition is a biometric technology to identify individual by using fingerprint features such ridges and valleys. Most fingerprint systems perform the recognition based on minutiae points after acquiring a fingerprint image from contact type sensor. They have an advantage of acquiring a clear image of uniform size by touching finger on the sensor. However, they have the problems of the image quality can be reduced in case of severely dry or wet finger due to the variations of touching pressure and latent fingerprint on the sensor. To solve these problems, the contactless capturing devices for a fingerprint image was introduced in previous works. However, the accuracy of detecting minutiae points and recognition performance are reduced due to the degradation of image quality by the illumination variation. So, this paper proposes a new LDP-based fingerprint recognition method. It can effectively extract fingerprint patterns of iterative ridges and valleys. After producing histograms of the binary codes which are extracted by the LDP method, chi square distance between the enrolled and input feature histograms is calculated. The calculated chi square distance is used as the score of fingerprint recognition. As the experimental results, the EER of the proposed approach is reduced by 0.521% in comparison with that of the previous LBP-based fingerprint recognition approach.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.49 no.4
• /
• pp.77-84
• /
• 2012

Face classification has wide applications in intelligent video surveillance, content retrieval, robot vision, and human-machine interface. Pose and expression changes, and arbitrary illumination are typical problems for face recognition. When the face is captured at a distance, the image quality is often degraded by blurring and noise corruption. This paper investigates the efficacy of multi-classifier decision level fusion for face classification based on the photon-counting linear discriminant analysis with two different cost functions: Euclidean distance and negative normalized correlation. Decision level fusion comprises three stages: cost normalization, cost validation, and fusion rules. First, the costs are normalized into the uniform range and then, candidate costs are selected during validation. Three fusion rules are employed: minimum, average, and majority-voting rules. In the experiments, unfocusing and motion blurs are rendered to simulate the effects of the long distance environments. It will be shown that the decision-level fusion scheme provides better results than the single classifier.