• Journal of Korea Multimedia Society
• /
• v.24 no.1
• /
• pp.146-154
• /
• 2021

Conspicuous consumption is often investigated in Korea and consumers purchase a product to publicly display economic power or social status. The existing studies argue that brand loyalty and luxury brand preferences escalate conspicuous consumption, and it is important to identify different visual perception to understand irrational consumers' behavior. Car emblem as brands' visual identity represents the brand's image, mission and message. Irrational consumers thus are expected have different visual perception to the emblem or logo. To understand the impact of irrational consumer behavior on visual perception, this study explored how brand loyalty and luxury brand preferences impact on the visual perception of car emblems between Korean domestic brand and imported brand. This study used eye tracking technology to measure the respondents' attention on an emblem of the cars. Eye tracking tools analyze fixations and measure the attention on a specific area of interests (AOI). This study explored the maintaining time and frequency on AOI, as well as explored the size of pupil to identify the respondents' attention on the AOI. In this experiment, the logos of domestic cars (i.e., Hyundai and Kia) and foreign cars (i.e., Mercedes-Benz and BMW) were swapped to see how irrational consumer behavior impact on visual perception of car emblem.

• Journal of Platform Technology
• /
• v.10 no.1
• /
• pp.20-28
• /
• 2022

Artificial intelligence-based health data verification has become an essential element not only to help clinical research, but also to develop new treatments. Since the US Food and Drug Administration (FDA) approved the marketing of medical devices that detect mild abnormal diabetic retinopathy in adult diabetic patients using artificial intelligence in the field of medical diagnosis, tests using artificial intelligence have been increasing. In this study, an artificial intelligence model based on image classification was created using a Teachable Machine supported by Google, and a predictive model was completed through learning. This not only facilitates the early detection of cataracts among eye diseases occurring among patients with chronic diseases, but also serves as basic research for developing a digital personal health healthcare app for eye disease prevention as a healthcare program for eye health.

• Current Optics and Photonics
• /
• v.6 no.2
• /
• pp.151-160
• /
• 2022

Fundus images can reflect ocular diseases and systemic diseases such as glaucoma, diabetes mellitus, and hypertension. Thus, research on fundus-detection equipment is of great importance. The fundus camera has been widely used as a kind of noninvasive detection equipment. Most existing devices can only obtain two-dimensional (2D) retinal-image information, yet the fundus of the human eye also has spectral characteristics. The fundus has many pigments, and their different distributions in the eye lead to dissimilar tissue penetration for light waves, which can reflect the corresponding fundus structure. To obtain more abundant information and improve the detection level of equipment, a snapshot nonmydriatic fundus imaging spectral system, including fundus-imaging spectrometer and illumination system, is studied in this paper. The system uses a microlens array to realize snapshot technology; information can be obtained from only a single exposure. The system does not need to dilate the pupil. Hence, the operation is simple, which reduces its influence on the detected object. The system works in the visible and near-infrared bands (550-800 nm), with a volume less than 400 mm × 120 mm × 75 mm and a spectral resolution better than 6 nm.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.43 no.1 s.343
• /
• pp.65-70
• /
• 2006

An image sensor has limited dynamic range while the human eye has logarithmic response over wide range of light intensity. Although the sensor gain can be set high to identify details in darker area on the image, this results in saturation in brighter area. The gamma correction is essential to fit the human eye response. However, the digital gamma correction degrades image quality especially for darker area on the image due to the limited ADC resolution and the dynamic range. This Paper proposes a CMOS image sensor (CIS) with a nonlinear analog-to-digital converter (AU) which performs analog gamma correction. The CIS with the proposed nonlinear analog-to-digital conversion scheme was fabricated with a $0.35{\mu}m$ CMOS process. The analog gamma correction using the proposed nonlinear ADC CIS provides the 2.2dB peak-signal-to-noise-ratio(PSM) improved image qualify than conventional digital gamma correction. The PSNR of the image obtain from the digital gamma correction is 25.6dB while it is 27.8dB for analog gamma correction. The PSNR improvement over digital gamma correction is about $28.8\%$.

• Journal of the Korean Society of Fashion and Beauty
• /
• v.2 no.2 s.2
• /
• pp.59-70
• /
• 2004

The purpose of this study were to find out appeal types and variation of make-up image and make-up style in cosmetics advertising. The research of this study were collected from cosmetics advertisement printed in Amole Pacific Cosmetic industry from $1970{\sim}2004$. The results were as follow: 1. A cosmetics advertisement appeal were three types. it were models and products appeal advertisement as emotional appeal, products-appeal and mixed appeal advertisement. 2. A variation of make-up image were different by the time. In the 1970s make-up were model empersis eye-line and colorful make-up were classic and active make-up image. From the 1980s various color make-up were used and persuited of individuality and started to appeal that were romantic and elegance image. In the 1990s multi-color make-up image were manish and modern used ambivalence and multi-message, and in the $2000{\sim}2004$ natural and romantic-sexy remarkable make-up image were used of new concept of beauty.

• Electronics and Telecommunications Trends
• /
• v.35 no.4
• /
• pp.91-102
• /
• 2020

Recently, generative adversarial networks (GANs) is a field of research that has rapidly emerged wherein many studies conducted shows overwhelming results. Initially, this was at the level of imitating the training dataset. However, the GAN is currently useful in many fields, such as transformation of data categories, restoration of erased parts of images, copying facial expressions of humans, and creation of artworks depicting a dead painter's style. Although many outstanding research achievements have been attracting attention recently, GANs have encountered many challenges. First, they require a large memory facility for research. Second, there are still technical limitations in processing high-resolution images over 4K. Third, many GAN learning methods have a problem of instability in the training stage. However, recent research results show images that are difficult to distinguish whether they are real or fake, even with the naked eye, and the resolution of 4K and above is being developed. With the increase in image quality and resolution, many applications in the field of design and image and video editing are now available, including those that draw a photorealistic image as a simple sketch or easily modify unnecessary parts of an image or a video. In this paper, we discuss how GANs started, including the base architecture and latest technologies of GANs used in high-resolution, high-quality image creation, image and video editing, style translation, content transfer, and technology.

• New & Renewable Energy
• /
• v.9 no.3
• /
• pp.14-19
• /
• 2013

Comparative evaluation of offshore wind retreival software, which use the satellite images taken by Synthetic Aperture Radar sensor; SARTools of CLS-SOPRONO, France and SpaceEye of London Research and Development Corporation, Canada is carried out. For a reference satellite image, ENVISAT ASAR imagery of Jeollanam-do Wan-do area when the winter-time northwestern wind prevails is processed by CMOD_IFR2, CMOD4, CMOD5 algorithms. Wind speed difference and its relative ratio are calculated to evaluate uncertainty of software selection.

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.77.4-77
• /
• 2002

Communicating devices for the seriously disabled using eye-ball movement or some body movement are proposed. The first one is a device to use image processing, whose input signal is eyeball movement, A feature of this device is that the device can be readily realized using a note-book computer with USB (Universal Serial Bus) interface bus. This device is incorporated with a word processing software called Nearly Ladder. The second one is an emergency call switch which is used by a patient who can move his finger slightly. The patients can switch on the emergency switch only by touching a switch with his finger. The essence of this sensor is a touch sensor. The sensor can be realized using onl...

• Proceedings of the IEEK Conference
• /
• 2003.07b
• /
• pp.847-850
• /
• 2003

An Eye Ball Sensor (EBS) is a system that locates the point where the user gazes on. The conventional EBS using a CCD camera needs many peripherals, software computation causing high cost and power consumption. This paper proposes a compact EBS using smart CMOS Image Sensor (CIS) pixels. The proposed single chip EBS does not need any peripheral and operates at higher speed and lower cost than the conventional EBS. The test chip was designed and fabricated for 32$\times$32 smart CIS pixel array with a 0.35 um CMOS process occupying 5.3$\textrm{mm}^2$ silicon area.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.11-14
• /
• 2000

In this paper, we propose a fast and practical head pose estimation scheme fur eye-head controlled human computer interface with non-constrained background. The method we propose uses complete graph matching from thresholded images and the two blocks showing the greatest similarity are selected as eyes, we also locate mouth and nostrils in turn using the eye location information and size information. The average computing time of the image(360*240) is within 0.2(sec) and we employ template matching method using angles between facial features for head pose estimation. It has been tested on several sequential facial images with different illuminating conditions and varied head poses, It returned quite a satisfactory performance in both speed and accuracy.