• Journal of Biosystems Engineering
• /
• v.17 no.4
• /
• pp.382-395
• /
• 1992

The surface color of several varieties of apples were expressed quantitatively in xyz chromaticity coordinates. The spectral reflectance of 'Fuji' apples were measured in 400-820 nm range by using a spectrophotometer. Based on the spectrophotometer data and the result of visual sensory test, linear regression models were developed to select wavelengths effective for sorting apples. The models utilized reflectance at single wavelength, and the difference and ratio of the reflectance at two distinct wavelengths. The model which best fitted the visual sensory test data was one utilizing the ratio of the reflectance at 618 nm and 514nm. The correlation coefficient for this model was 0.967. Several other models were also described.

• Smart Structures and Systems
• /
• v.31 no.4
• /
• pp.351-363
• /
• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• Journal of the Korean Society of Costume
• /
• v.58 no.9
• /
• pp.81-98
• /
• 2008

This research aims to analyze humorous images expressed in 2D graphics fashion illustrations and to propose application of 2D graphics in humorous images for fashion illustrations to suggest a more creative and relevant fashion illustration for contemporary culture. The result of this research were as follows: First, theories on reaction of humor can be classified into Incongruity theory, Superiority theory and Arousal and Relief theory. Humor in visual arts are classified in Visual Parody, Visual Pun, Visual Paradox and Visual Satire. Second, Visual Pun, Visual Parody, and Visual Satire are used for visualizing fashion illustration, and the foundations for many humor images were simple-colored, imaginative, and unreal settings. And it was also found out that the physical proportion of the models generally was 1(head):7(entire body), 1:8, 1:15 and the models were usually laughing and smiling. Tone was usually pastel and vivid, and posture was usually standing-position or sitting-position. Third, based on such results, fashion illustration works of humor image using 2D graphics were created. To concretize the humor image, 'gift' as a concept was chosen. Humor alleviates the tension and stress. It also brings laughter and pleasure to people's lives. Therefore humor image will be an effective way of expanding creativity in modern fashion illustration.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.38 no.6
• /
• pp.617-629
• /
• 2001

The mathematical models for the receptive field of simple cells in the human visual system have been developed in the areas of psychophysics, physiology and neuroscience. The various models used in the fields of digital image processing and computer vision include Gator complex, Gaussian derivatives and Hermite functions. In this paper, the effective widths for the models are derived based on the space-frequency uncertainty principle. The center frequency and parameters related to the models are determined in accordance with the human visual filters, and resultant bandwidths are analyzed. Furthermore, the characteristics of space and frequency for the models is analyzed and compared to the experimental data obtained from psychophysics.

• Proceedings of the IEEK Conference
• /
• 2001.06d
• /
• pp.239-242
• /
• 2001

As systems for real time computer vision are confronted with prodigious amounts of visual information, it has become a priority to locate and analyze just that information essential to the task at hand, while ignoring the vast flow of irrelevant detail. A method of achieving this is to using human visual attention mechanism. In this paper, short review of human visual attention mechanisms and some computation models of visual attention were shown. This paper can be used as the basic data for researches on development of visual attention system that can perform various complex tasks more efficiently.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.5
• /
• pp.1220-1228
• /
• 1995

In this paper, we consider the problems of tracking an object in a real image. In evaluating these problems, we explore a new technique based on an active contour model commonly called a snake model, and propose the active bar models to represent target. Using this model, we simplified the target welection problems, reduced the search space of energy surface, and obtained the better performances than those of snake model. This approach improves the numerical stability and the tendency for points to bunch up and speed up the computational efficiency. Representing the object by active bar, we can easily obtain the zeroth, the first, and the second moment and it facilitates the target tracking. Finally, we present the good result for the visual tracking problem.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.8
• /
• pp.3791-3805
• /
• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

• Journal of the Ergonomics Society of Korea
• /
• v.26 no.2
• /
• pp.149-155
• /
• 2007

Recently, various devices requiring text input such as mobile phone IPTV, PDA and UMPC are emerging. The frequency of text entry for them is also increasing. This study was focused on the evaluation of Korean text entry interface. Various models to evaluate text entry interfaces have been proposed. Most of models were based on human cognitive process for text input. The cognitive process was divided into two components; visual scanning process and finger movement process. The time spent for visual scanning process was modeled as Hick-Hyman law, while the time for finger movement was determined as Fitts' law. There are three questions on the model-based evaluation of text entry interface. Firstly, are human cognitive processes (visual scanning and finger movement) during the entry of text sequentially occurring as the models. Secondly, is it possible to predict real text input time by previous models. Thirdly, does the human cognitive process for text input vary according to users' text entry speed. There was time gap between the real measured text input time and predicted time. The time gap was larger in the case of participants with high speed to enter text. The reason was found out investigating Eye-Hand Coordination during text input process. Differently from an assumption that visual scan on the keyboard is followed by a finger movement, the experienced group performed both visual scanning and finger movement simultaneously. Arrival Lead Time was investigated to measure the extent of time overlapping between two processes. 'Arrival Lead Time' is the interval between the eye fixation on the target button and the button click. In addition to the arrival lead time, it was revealed that the experienced group uses the less number of fixations during text entry than the novice group. This result will contribute to the improvement of evaluation model for text entry interface.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2011.11a
• /
• pp.56-58
• /
• 2011

• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.273-276
• /
• 2002

Pulse-Coupled Neural Network (PCNN), which can explain the synchronous burst of neurons in a cat visual cortex, is a fundamental model for the biomimetic vision. The PCNN is a kind of pulse coded neural network models. In order to get deep understanding of the visual information Processing, it is important to simulate the visual system through such biologically plausible neural network model. In this paper, we construct the motion detection model based on the PCNN with the receptive field models of neurons in the lateral geniculate nucleus and the primary visual cortex. Then it is shown that this motion detection model can detect the movements and the direction of motion effectively.