• 제목/요약/키워드: image technology

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A Research on AI Generated 2D Image to 3D Modeling Technology

  • Ke Ma;Jeanhun Chung
    • International Journal of Internet, Broadcasting and Communication
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    • v.16 no.2
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    • pp.81-86
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    • 2024
  • Advancements in generative AI are reshaping graphic and 3D content design landscapes, where AI not only enriches graphic design but extends its reach to 3D content creation. Though 3D texture mapping through AI is advancing, AI-generated 3D modeling technology in this realm remains nascent. This paper presents AI 2D image-driven 3D modeling techniques, assessing their viability in 3D content design by scrutinizing various algorithms. Initially, four OBJ model-exporting AI algorithms are screened, and two are further evaluated. Results indicate that while AI-generated 3D models may not be directly usable, they effectively capture reference object structures, offering substantial time savings and enhanced design efficiency through manual refinements. This endeavor pioneers new avenues for 3D content creators, anticipating a dynamic fusion of AI and 3D design.

Visual Saliency Detection Based on color Frequency Features under Bayesian framework

  • Ayoub, Naeem;Gao, Zhenguo;Chen, Danjie;Tobji, Rachida;Yao, Nianmin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.2
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    • pp.676-692
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    • 2018
  • Saliency detection in neurobiology is a vehement research during the last few years, several cognitive and interactive systems are designed to simulate saliency model (an attentional mechanism, which focuses on the worthiest part in the image). In this paper, a bottom up saliency detection model is proposed by taking into account the color and luminance frequency features of RGB, CIE $L^*a^*b^*$ color space of the image. We employ low-level features of image and apply band pass filter to estimate and highlight salient region. We compute the likelihood probability by applying Bayesian framework at pixels. Experiments on two publically available datasets (MSRA and SED2) show that our saliency model performs better as compared to the ten state of the art algorithms by achieving higher precision, better recall and F-Measure.

AgeCAPTCHA: an Image-based CAPTCHA that Annotates Images of Human Faces with their Age Groups

  • Kim, Jonghak;Yang, Joonhyuk;Wohn, Kwangyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.3
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    • pp.1071-1092
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    • 2014
  • Annotating images with tags that describe the content of the images facilitates image retrieval. However, this task is challenging for both humans and computers. In response, a new approach has been proposed that converts the manual image annotation task into CAPTCHA challenges. However, this approach has not been widely used because of its weak security and the fact that it can be applied only to annotate for a specific type of attribute clearly separated into mutually exclusive categories (e.g., gender). In this paper, we propose a novel image annotation CAPTCHA scheme, which can successfully differentiate between humans and computers, annotate image content difficult to separate into mutually exclusive categories, and generate verified test images difficult for computers to identify but easy for humans. To test its feasibility, we applied our scheme to annotate images of human faces with their age groups and conducted user studies. The results showed that our proposed system, called AgeCAPTCHA, annotated images of human faces with high reliability, yet the process was completed by the subjects quickly and accurately enough for practical use. As a result, we have not only verified the effectiveness of our scheme but also increased the applicability of image annotation CAPTCHAs.

Multiscale self-coordination of bidimensional empirical mode decomposition in image fusion

  • An, Feng-Ping;Zhou, Xian-Wei;Lin, Da-Chao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.4
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    • pp.1441-1456
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    • 2015
  • The bidimensional empirical mode decomposition (BEMD) algorithm with high adaptability is more suitable to process multiple image fusion than traditional image fusion. However, the advantages of this algorithm are limited by the end effects problem, multiscale integration problem and number difference of intrinsic mode functions in multiple images decomposition. This study proposes the multiscale self-coordination BEMD algorithm to solve this problem. This algorithm outside extending the feather information with the support vector machine which has a high degree of generalization, then it also overcomes the BEMD end effects problem with conventional mirror extension methods of data processing,. The coordination of the extreme value point of the source image helps solve the problem of multiscale information fusion. Results show that the proposed method is better than the wavelet and NSCT method in retaining the characteristics of the source image information and the details of the mutation information inherited from the source image and in significantly improving the signal-to-noise ratio.

Relationship Between Image Quality and Changes in Spation Resolution for the Gamma Camera (감마카메라의 공간분해능 변화와 화질과의 관계)

  • Lee, Man-Koo;Park, Soung-Ock
    • Journal of radiological science and technology
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    • v.25 no.1
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    • pp.77-81
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    • 2002
  • The purpose of this study is to examine quantitatively the relationship between visual image quality and degradation In spatial resolution for a gamma camera by the increase in distance from collimator. The relationship between the portion(p) of images identified the difference of image quality and the difference(${\Delta}FWHM$) in FWHM between paired images was showed in a sigmoid curve. Using Dendy's method, minimum level to be correctly identified the difference of Image duality on three out of four occasion(p=0.75) was corresponded to 0.4 mm in ${\Delta}FWHM$. Using fuzzy theory, the level to be identified the difference of image quality was examined under various conditions. The truth-value of fuzzy sets-degraded or slightly degraded and not-degraded in image quality between palled Images-was gained the peak at 0.5 mm of ${\Delta}FWHM$. It was founded that changes of $0.4{\sim}0.5\;mm$ in FWHM-corresponding about 2 cm distance from collimator could be sufficiently identified in the difference of image quality.

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Depth Extraction of Partially Occluded 3D Objects Using Axially Distributed Stereo Image Sensing

  • Lee, Min-Chul;Inoue, Kotaro;Konishi, Naoki;Lee, Joon-Jae
    • Journal of information and communication convergence engineering
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    • v.13 no.4
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    • pp.275-279
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    • 2015
  • There are several methods to record three dimensional (3D) information of objects such as lens array based integral imaging, synthetic aperture integral imaging (SAII), computer synthesized integral imaging (CSII), axially distributed image sensing (ADS), and axially distributed stereo image sensing (ADSS). ADSS method is capable of recording partially occluded 3D objects and reconstructing high-resolution slice plane images. In this paper, we present a computational method for depth extraction of partially occluded 3D objects using ADSS. In the proposed method, the high resolution elemental stereo image pairs are recorded by simply moving the stereo camera along the optical axis and the recorded elemental image pairs are used to reconstruct 3D slice images using the computational reconstruction algorithm. To extract depth information of partially occluded 3D object, we utilize the edge enhancement and simple block matching algorithm between two reconstructed slice image pair. To demonstrate the proposed method, we carry out the preliminary experiments and the results are presented.

Development of ResNet-based WBC Classification Algorithm Using Super-pixel Image Segmentation

  • Lee, Kyu-Man;Kang, Soon-Ah
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.4
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    • pp.147-153
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    • 2018
  • In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

Implementation of an improved real-time object tracking algorithm using brightness feature information and color information of object

  • Kim, Hyung-Hoon;Cho, Jeong-Ran
    • Journal of the Korea Society of Computer and Information
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    • v.22 no.5
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    • pp.21-28
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    • 2017
  • As technology related to digital imaging equipment is developed and generalized, digital imaging system is used for various purposes in fields of society. The object tracking technology from digital image data in real time is one of the core technologies required in various fields such as security system and robot system. Among the existing object tracking technologies, cam shift technology is a technique of tracking an object using color information of an object. Recently, digital image data using infrared camera functions are widely used due to various demands of digital image equipment. However, the existing cam shift method can not track objects in image data without color information. Our proposed tracking algorithm tracks the object by analyzing the color if valid color information exists in the digital image data, otherwise it generates the lightness feature information and tracks the object through it. The brightness feature information is generated from the ratio information of the width and the height of the area divided by the brightness. Experimental results shows that our tracking algorithm can track objects in real time not only in general image data including color information but also in image data captured by an infrared camera.

A Study of Image Enhancement Processing for Letter Extraction of Image Using Terahertz Signal (테라헤르츠 신호를 이용한 영상의 글자 추출을 위한 화질 개선처리에 대한 연구)

  • Kim, Seongyoon;Choi, Hyunkeun;Park, Inho;Kim, Youngseop;Lee, Yonghwan
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.3
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    • pp.111-115
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    • 2017
  • Terahertz waves are superior to conventional X-ray or Magnetic Resonance Tomography(MRI), and the amount of information that can be transmitted is as large as thousands of times that conventional X-ray or MRI. In addition, Terahertz waves have great performance in analyzing an object which have some layered structure. By using this advantage, we can extract the letters of a page by analyzing information such as absorption amount and reflection amount by irradiating a closed book with pulses of various frequencies within gap of a terahertz wave. However, in the image of each page using the Terahertz wave might be obtained various kinds of noise and the different character occlusion region. So, to extract letters from the terahertz image, we must take the noise and occlusion region away. We have been working to enhancement the image quality in various ways, and keep on studying de-noising processing for enhancement about the image quality and high resolution. Finally, we also keep on studying about OCR(Optical Character Recognition) technology, which based on pattern matching technique, to read letters.

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Image Analysis for the Simultaneous Measurement of Underwater Flow Velocity and Direction (수중 유속 및 유향의 동시 측정을 위한 이미지 분석 기술에 관한 연구)

  • Dongmin Seo;Sangwoo Oh;Sung-Hoon Byun
    • Journal of Sensor Science and Technology
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    • v.32 no.5
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    • pp.307-312
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    • 2023
  • To measure the flow velocity and direction in the near field of an unmanned underwater vehicle, an optical measurement unit containing an image sensor and a phosphor-integrated pillar that mimics the neuromasts of a fish was constructed. To analyze pillar movement, which changes with fluid flow, fluorescence image analysis was conducted. To analyze the flow velocity, mean force analysis, which could determine the relationship between the light intensity of a fluorescence image and an external force, and length-force analysis, which could determine the distance between the center points of two fluorescence images, were employed. Additionally, angle analysis that can determine the angles at which pixels of a digital image change was selected to analyze the direction of fluid flow. The flow velocity analysis results showed a high correlation of 0.977 between the external force and the light intensity of the fluorescence image, and in the case of direction analysis, omnidirectional movement could be analyzed. Through this study, we confirmed the effectiveness of optical flow sensors equipped with phosphor-integrated pillars.