• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.1-9
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• 2010

In this paper we present a shading technique for realistic rendering of the surfaces with irregular and complex textures using a single photograph. So far, most works have been using many photographs or special photographing equipment to render the surfaces with irregular and complex textures as well as dividing texture regions manually. We present an automatic selection method of the region segmentation techniques according to properties of materials. As our technique produces a reflectance model and the approximated Bidirectional Reflection Distribution Function(BRDF) parameters, it allows the recovery of the photometric properties of diffuse, specular, isotropic or anisotropic textured objects. Also it make it possible to present several synthetic images with novel lighting conditions and views.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.77-82
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• 2021

There are three types of urinalysis: physical test, chemical test, and microscopic test. Among these, the chemical urinalysis is an easily accessible method of the general public to compare the chemical reaction of urinalysis strip with a standard colorimetric table by sight or purchase the portable urinalysis machine separately. Currently, with the popularization of smartphone, research on the urinalysis service using smartphone is increasing. The urinalysis screening application is one of the urinalysis services using a smartphone. However, the RGB values of the urinalysis pad taken by the urinalysis screening application have large deviations due to the effect of lighting. Deviation of RGB value debases the accuracy of urinalysis discrimination. Therefore, in this paper, the accuracy of urinaylsis pad image discrimination is improved through CNN after classifying urinalysis strips taken by the urinalysis screening application based on smartphone by urinalysis pad items. Urinalysis strip was taken from various backgrounds to generate CNN image, and urinalysis discrimination was analyzed using the ResNet-50 CNN model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.697-699
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• 2005

본 논문에서는 실세계 조명 정보를 표현하는 HDR(High Dynamic Range) 영상으로부터 소수의 방향성 광원을 추정하는 기법을 제안한다. 광원 추정을 위해 노출 시간을 달리한 일련의 일반 영상으로부터 실세계의 조명 정보를 선형적으로 표현할 수 있는 HDR영상을 생성한다. HDR영상의 색상 및 명도 변화를 이용하며 영역을 분할하고, 분할된 영역으로부터 명도 평균과 가중치를 이용하여 방향성 광원의 파라미터를 추출하는 방법을 제안한다. 제안된 방법의 장정은 비반복적인 기법을 사용하여 일관된 결과를 산출하여 사용자의 입력없이 자동으로 계산하는 것이다. 추정된 광원은 그래픽 하드웨어를 사용한 실시간 렌더링에 적용 가능하다. 또한 실시간 렌더링이 중요한 가상현실이나 증강현실 분야에서 가상의 오브젝트를 렌더링할 때 IBL(Image Based Lighting)등의 전역조명 효과와 유사한 사실적인 영상을 얻을 수 있다.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.395-399
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• 2006

A method to recognize unpaved road region using a 3D depth measurement system is proposed for mobile robots. For autonomous maneuvering of mobile robots, recognition of obstacles or recognition of road region is the essential task. In this paper, the 3D depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Therefore, the problem falls into a texture identification problem. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of unpaved trail are included in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.644-647
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• 2003

This paper describes a neural network based machine vision system designed for inspecting yellow beans in real time. The system consists of a camera. lights, a belt conveyor, air ejectors, and a computer. Beans are conveyed in four lines on a belt and their images are taken by a monochrome line scan camera when they fall down from the belt. Beans are separated easily from their background on images by back-lighting. After analyzing the image, a decision is made by a multilayer artificial neural network (ANN) trained by the error back-propagation (EBP) algorithm. We use the global mean, variance and local change of gray levels of a bean for the input nodes of the network. In an our experiment, the system designed could process about 520kg/hour.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.1
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• pp.125-133
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• 2017

Color in an image is determined by illuminant and surface reflectance. So, to recover unique color of object, estimation of exact illuminant is needed. In this study, the illumination models suggested to get the object color constancy with the physical illumination model based on physical phenomena. Their characteristics and application limits are presented and the necessity of an extended illumination model is suggested to get more appropriate object colors recovered. The extended illumination model should contain an additional term for the ambient light in order to account for spatial variance of illumination in object images. Its necessity is verified through an experiment under simple lighting environment in this study. Finally, a reconstruction method for recovering input images under standard white light illumination is experimented and an useful method for computing object color reflectivity is suggested and experimented which can be induced from combination of the existing illumination models.

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

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.6-9
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• 2008

A 3D depth measurement system is proposed for mobile vehicles. Depth measurement system which is composed of a rotating mirror, a line laser and mono-camera is employed to detect depth, where the laser light is reflected by the mirror and projected to- the scene objects whose locations are to be determined. The obtained depth information is converted into an image. Such depth images of the road region represent even and plane while that of off-road region is irregular or textured. Road region is detected employing a simple spatial differentiation technique to detect the plain textured area. Identification results of the diverse situation of Non-linear trail are included in this paper.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.300-302
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• 2006

The structured lighting technique is a very accurate depth measurement method. One problem in this technique is that the laser light is invisible very often partly or as a whole caused from occlusion, light absorbtion, and reflection on the surface. If there is no laser light detected on a row of the image frame, the depth could not be computed at the point on the row. In this paper, a Dynamic Programing-based efficient laser line tracking algorithm is proposed to find the most likely line of the laser light utilizing all the possible information of the laser light trace. The performance of the algorithm is shown.