Purpose: This study aimed to compare and assess whether there was a relation between self-reported symptom and stereopsis in viewing an anaglyph 3D and a general 2D image. Methods: Seventy subjects (38 males, 32 females) were students ranging in age from 20 to 30 years. Subjects' symptoms were investigated by a questionnaire after viewing the 2D image and the anaglyph 3D image using red-green glasses for 30 minutes. Titmus circles and TNO stereopsis tests were performed before and after the images. A correlation between symptom and stereopsis was evaluated. Results: Both ocular and nonocular symptom in viewing 3D image were higher than those in 2D image. Titmus circles stereopsises using polarized filters were not changed before and after viewing images, but TNO stereopsises using color filters such as red-green glasses were increased after viewing 3D image. Ocular symptom and TNO stereopsis were increased after viewing 3D image, and there was a good correlation between them (r=0.605). Conclusions: Better stereopsises before viewing 3D are relatively lower ocular symptoms in viewing 3D image. But symptoms are increased in viewing anaglyph 3D image for a short-time and improvement of TNO steropsis is poorly associated with the relief of ocular symptoms. This tendency seems to be related with an adaptation to anaglyph 3D image with red-green glasses.
A face detection algorithms using two-dimensional (2-D) intensity or color images have been studied for decades. Recently, with the development of low-cost range sensor, three-dimensional (3-D) information (i.e., depth image that represents the distance between a camera and objects) can be easily used to reliably extract facial features. Most people have a similar pattern of 3-D facial structure. This paper proposes a face detection method using intensity and depth images. At first, adaboost algorithm using intensity image classifies face and nonface candidate regions. Each candidate region is divided into $5{\times}5$ blocks and depth values are averaged in each block. Then, $5{\times}5$ block rank pattern is constructed by sorting block averages of depth values. Finally, candidate regions are classified as face and nonface regions by matching the constructed depth map based block rank patterns and a template pattern that is generated from training data set. For template matching, the $5{\times}5$ template block rank pattern is prior constructed by averaging block ranks using training data set. The proposed algorithm is tested on real images obtained by Kinect range sensor. Experimental results show that the proposed algorithm effectively eliminates most false positives with true positives well preserved.
Journal of the Korea Fashion and Costume Design Association
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v.5
no.2
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pp.75-91
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2003
This study analyzed descriptions about dots, lines, and sides which are used as a basic elements to express geometric figures as followings: -In the aspect of formative art, dots form images and feelings through their concurrence when make a slight move to coordinates. The concurrence can bring out either positive or negative images; -Lines have unlimited variation as a core measure in body art. They can make optimal effects with different lines such as straight and curved lines of human body; -Sides express not only effects of texture and perspective but also of space and solid by color effects. Expressive characteristics and geometric shapes can be classified by tattoo, henna and body painting: First, colorful tattoos are favored by Caucasian and original tattoos are mostly used by yellow and colored races in the way of scarification to get decorative effects. Recently, a rapid cycle of fashion change in tattoo figures has developed a tentative method of tattooing and a variety of decoration methods. It has made it a lot easier to change a pattern of a tattoo. Tattoos are now popular among people because they no longer have to suffer from pains when they get their body tattooed for a long time. Since tattoos boast their unique beauty which consists of most dynamic and attractive images among the types of body art. It will be one of the most favored make-up methods in the nearest future. Second, geometric designs used in henna include crosses, dots, straight lines, triangles, date palms, and so on. Henna has been particularly loved as an instant decoration by the public since it gradually disappears as time goes on. Third, body painting enables to draw a three-dimensional effect because of its close relation with body movements in a limited space. Each individual will have a different feeling appealed in their body painting. Body painting has been applied to many different areas, especially to theatrical art using lights, music and performance altogether producing impromptu and experimental works. Unlike other arts such as painting, sculpture, visual and industrial arts, body painting has mobility. Since it is painted on a three-dimensional human body, it can bear originality expressing realistic objects or animals and strengthen creative functions using body lines. Moreover, geometric designs can be diversified by the sexes. As a result of analysis, geometric designs expressed in body art seemed to transcend expressions of beauty and turned out to be another way of decoration. Body art has also been used as a way to express visual integration and consolidation dynamically not by human instinct but by social changes. The needs for body art will grow as the future comes nearer and be recognized as a new and fresh value. Formative elements of geometric figures deliver visual impressions combined with human body and finally create more various types of body art in harmony of body lines.
To analyze the distribution pattern of flood sediment deposits near the mouth of Chucheoncheon (river), side scan sonar images and seafloor sediment properties were investigated in the offshore area within about 50 m deep in water. Based on the analysis result of the sonar images, the seafloor of the study area is divided into three areas of basement, sandy-mud, and dispersed flood sediment. The colors of sonar images in each area are represented by dark black, light grey, and greyish black, respectively. The sediment composition in the grey black area shows 33.73% of gravel, 62.88% of sand, 3.37% of silt, and 0.02% of clay. On the other hand, the composition of the light grey area is 10.31% of sand, 56.42% of silt, and 33.27% of clay. Especially the sediment of the grey black area contains the considerable amount of burned plant fragments in black color, which could distinctly be differentiated from those in the offshore. The distribution pattern of the flood sediment deposits suggests that the land-originated detrital sediments seem to be transported from the Chucheon river into offshore along the shore rather than transversely. In conclusion, the longshore current of the study area is probably dominant to affect the spatial distribution of bottom features.
'Naturalness' is the important "ness" which is a key factor in image quality assessment. 'Naturalness' is a representive factor depending on the context of the image which arouses different emotions. The Image Quality Circle was split into two steps. The first step is predicting the visual perceptual attribute which are lightness, colourfulness, hue and contrast. The next step is SSE which is dependent to image contents. In this study the image contents are grouped in genres. The images were rendered using four different colour attributes which are lightness, contrast, colourfulness and hue. Using a scale, the score of image quality and SSE was asked to each participant for all rendered images. A seven-point category scale of increasing amount of "ness" is used as a quantitative adjectives sequence. The image quality model was built by combining the SSEs for each scene. The SSEs, where vividness is common, are considered as independent variables to predict the image quality score. Then the vividness model was built using colour attributes as variables to predict the vividness of each scene (genre). Vividness is an important factor of naturalness which the meaning is different for all scenes that links the naturalness and image quality. The vividness meaning was different for each scene (genre). Therefore, the colour attributes that express the vividness would depend on the image content.
Journal of the Korean Institute of Intelligent Systems
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v.26
no.5
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pp.423-431
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2016
In general LPR(License Plate Recognition) in outdoor image is not so simple differently from in the image captured from manmade environment, because of geometric shape distortion and large illumination changes. this paper proposes three techniques for LPR in outdoor images captured from CCTV. At first, a serially connected multi-stage Adaboost LP detector is proposed, in which different complementary features are used. In the proposed detector the performance is increased by the Haar-like Adaboost LP detector consecutively connected to the MB-LBP based one in serial manner. In addition the technique is proposed that makes image processing easy by the prior determination of LP type, after correction of geometric distortion of LP image. The technique is more efficient than the processing the whole LP image without knowledge of LP type in that we can take the appropriate color to gray conversion, accurate location for separation of text/numeric character sub-images, and proper parameter selection for image processing. In the proposed technique we use DBN(Deep Belief Network) to achieve a robust character recognition against stroke loss and geometric distortion like slant due to the incomplete image processing.
Proceedings of the Korean Institute of Navigation and Port Research Conference
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2002.11a
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pp.147-153
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2002
Due to the growth of population and industrial development at the coastal cities, there has been much increase in necessity to effective control of the wastes into the coastal water and river. The amount of disposal at those waters has been increased rapidly and it is necessary for us to track of it in order to keep the water clean. The investigation and research related to the water quality in this region have been conducted continuously but the systematic survey of the disposed wastes at the bottom was neglected and/or minor. In this study we surveyed the status of disposed waste distribution at the bottom coastal water and river from the scanned images. The intensity of sound received by the side scan sonar tow vehicle from the sea floor provides information as to the general distribution and characteristics of the superficial wastes. The port and starboard side scanned images produced from a transducer borne on a tow fish connected by tow cable to a tug boat have the area with width of 22m∼112m, and band of 44m∼224m. All data are displayed in real-time on a high-resolution color display (1280 ${\times}$ 1024 pixels) together with position information by DGPS. From the field measurement and analysis of the recorded images, we could draw the location and distribution of bottom disposals. Furthermore, we made a database system which might be fundamental for planning the waste reception and process control system.
For medical students and doctors, knowledge of the 3-dimensional (3D) structure of the heart is very important in diagnosis and treatment of the heart diseases. 2-dimensional (2D) tools (e.g. anatomy book) or classical 3D tools (e.g. plastic model) are not sufficient or understanding the complex structures of the heart. Moreover, it is not always guaranteed to dissect the heart of cadaver when it is necessary. To overcome this problem, virtual dissection systems of the heart have been developed. But these systems are not satisfactory since they are made of radiographs; they are not true 3D images; they can not be used to dissect freely; or they can only be operated on the workstation. It is also necessary to make the dissection systems incorporating the various races and tribes because of the organ's difference according to race and tribe. This study was intended to make the 3D image of the heart from a Korean cadaver, and to establish a virtual dissection system of the heart with a personal computer. The procedures or manufacturing this system were as follows. 1. The heart from a Korean adult cadaver was embedded with gelatin solution, and serially cross-sectioned at 1mm-thickness on a meat slicer. Pictures or 153 cross-sectioned specimens were inputted into the computer using a digital camera ($756{\times}504$ resolution, true color). 2. The alignment system was established by means of the language of IDL, and applied to align 2D images of the heart. In each of 2D images, closed curves lining clean and dirty blood pathways were drawn manually on the CorelDRAW program. 3. Using the language of IDL, the 3D image and the virtual dissection system of the heart were constructed. The virtual dissection system of the heart allowed or ree rotation, any-directional sectioning, and selected visualization of the heart's structure. This system is expected to become more advanced, and to be used widely through Internet or CD-title as an educational tool for medical students and doctors.
This paper presents a method to segment the object of interest from a set of multi-view images with minimal user interaction. Specifically, after the user segments an initial image, we first estimate the transformations between foreground and background of the segmented image and the neighboring image, respectively. From these transformations, we obtain regions in the neighboring image that respectively correspond to the foreground and the background of the segmented image. We are then able to segment the neighboring image based on these regions, and iterate this process to segment the whole image set. Transformation of foregrounds are estimated by feature-based registration with free-form deformation, while transformation of backgrounds are estimated by homography constrained to affine transformation. Here, both are based on correspondence point pairs. Segmentation is done by estimating pixel color distributions and defining a shape prior based on the obtained foreground and background regions and applying them to a Markov random field (MRF) energy minimization framework for image segmentation. Experimental results demonstrate the effectiveness of the proposed method.
This paper presents an automatic method to detect and count the cells from microorganism images based on mobile environments. Cell counting is an important process in the field of biological and pathological image analysis. In the past, cell counting is done manually, which is known as tedious and time consuming process. Moreover, the manual cell counting can lead inconsistent and imprecise results. Therefore, it is necessary to make an automatic method to detect and count cells from biological images to obtain accurate and consistent results. The proposed multi-step cell counting method automatically segments the cells from the image of cultivated microorganism and labels the cells by utilizing topological analysis of the segmented cells. To improve the accuracy of the cell counting, we adopt watershed algorithm in separating agglomerated cells from each other and morphological operation in enhancing the individual cell object from the image. The system is developed by considering the availability in mobile environments. Therefore, the cell images can be obtained by a mobile phone and the processed statistical data of microorganism can be delivered by mobile devices in ubiquitous smart space. From the experiments, by comparing the results between manual and the proposed automatic cell counting we can prove the efficiency of the developed system.
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