• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.578-581
• /
• 2006

Usually to achieve precise geolocation of satellite images, we need to get GCPs (Ground control points) from individual scenes. This requirement greatly increases the cost and processing time for satellite mapping. In this article, we focus on finding appropriate sensor models for entire image strips composing of several adjacent scenes. We tested the feasibility of modelling whole satellite image strips by establishing sensor models of one scene with GCPs and by applying the models to neighboring scenes without GCPs. For this, we developed two types of sensor models: collinearity-based type and orbit-based type and tested them using different sets of unknowns. Results indicated that although the performance of two types was very similar, for modelling individual scenes, it was not for modelling the whole strips. Moreover, the performance of sensor models was remarkably sensitive to different sets of unknowns. It was found that the orbit-based model using attitude biases as unknowns can be used to model SPOT image strips of 420 Km in length.

• ETRI Journal
• /
• v.29 no.2
• /
• pp.246-248
• /
• 2007

Query-by-example (QBE) is a well-known method for image retrieval. In reality, however, an example image to be used for the query is rarely available. Therefore, it is often necessary to find a good example image to be used for the query before applying the QBE method. Query-by-layout (QBL) is our proposal for that purpose. In particular, we make use of the visual descriptors such as the edge histogram descriptor (EHD) and the color layout descriptor (CLD) in MPEG-7. Since image features of the CLD and the EHD can be localized in terms of a$4{\times}4$ sub-image, we can specify image features such as color and edge distribution on each sub-image separately for image retrieval without a query image. Experimental results show that the proposed query method can be used to retrieve a good image as a starting point for further QBE-based image retrieval.

• Journal of Information Processing Systems
• /
• v.9 no.3
• /
• pp.499-510
• /
• 2013

Hardware-Software co-simulation of a multiple image encryption technique shall be described in this paper. Our proposed multiple image encryption technique is based on the Latin Square Image Cipher (LSIC). First, a carrier image that is based on the Latin Square is generated by using 256-bits of length key. The XOR operation is applied between an input image and the Latin Square Image to generate an encrypted image. Then, the XOR operation is applied between the encrypted image and the second input image to encrypt the second image. This process is continues until the nth input image is encrypted. We achieved hardware co-simulation of the proposed multiple image encryption technique by using the Xilinx System Generator (XSG). This encryption technique is modeled using Simulink and XSG Block set and synthesized onto Virtex 2 pro FPGA device. We validated our proposed technique by using the hardware software co-simulation method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.4
• /
• pp.1760-1778
• /
• 2018

For image segmentation with intensity inhomogeneity, many region-based level set methods have been proposed. Some of them however can't get the relatively ideal segmentation results under the severe intensity inhomogeneity and weak edges, and without use of the image gradient information. To improve that, we propose a new level set method combined with local direction gradient in this paper. Firstly, based on two assumptions on intensity inhomogeneity to images, the relationships between segmentation objects and image gradients to local minimum and maximum around a pixel are presented, from which a new pixel classification method based on weight of Euclidian distance is introduced. Secondly, to implement the model, variational level set method combined with image spatial neighborhood information is used, which enhances the anti-noise capacity of the proposed gradient information based model. Thirdly, a new diffusion process with an edge indicator function is incorporated into the level set function to classify the pixels in homogeneous regions of the same segmentation object, and also to make the proposed method more insensitive to initial contours and stable numerical implementation. To verify our proposed method, different testing images including synthetic images, magnetic resonance imaging (MRI) and real-world images are introduced. The image segmentation results demonstrate that our method can deal with the relatively severe intensity inhomogeneity and obtain the comparatively ideal segmentation results efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.11
• /
• pp.2175-2190
• /
• 2011

This paper presents the effects of depth map quantization for multiview intermediate image generation using depth image-based rendering (DIBR). DIBR synthesizes multiple virtual views of a 3D scene from a 2D image and its associated depth map. However, it needs precise depth information in order to generate reliable and accurate intermediate view images for use in multiview 3D display systems. Previous work has extensively studied the pre-processing of the depth map, but little is known about depth map quantization. In this paper, we conduct an experiment to estimate the depth map quantization that affords acceptable image quality to generate DIBR-based multiview intermediate images. The experiment uses computer-generated 3D scenes, in which the multiview images captured directly from the scene are compared to the multiview intermediate images constructed by DIBR with a number of quantized depth maps. The results showed that there was no significant effect on depth map quantization from 16-bit to 7-bit (and more specifically 96-scale) on DIBR. Hence, a depth map above 7-bit is needed to maintain sufficient image quality for a DIBR-based multiview 3D system.

• Journal of Digital Contents Society
• /
• v.5 no.4
• /
• pp.269-274
• /
• 2004

The field based morping requires the user to set most of the control lines manually which require much time and skill to get satisfactory results. This tjesis proposes a method to acquire semi-automation of image morphing through first acquiring shape information from the source image and the target image, than after the user manually designates the least amount of a pair of feature points, these are used as standards for polygon based vertex to set the appropriate control line to the source image and target image, and then using the ratio of control line lengths and space. Using the proposed method the user can reduce the time setting the control line and unskilled persons can get natural image morphing results while desingnating the least amount of control line.

• Journal of Biomedical Engineering Research
• /
• v.44 no.3
• /
• pp.176-181
• /
• 2023

During cancer treatment, the patient's response to drugs appears differently at the cellular level. In this paper, an image-based cell phenotypic feature quantification and key feature selection method are presented to predict the response of patient-derived cancer cells to a specific drug. In order to analyze the viability characteristics of cancer cells, high-definition microscope images in which cell nuclei are fluorescently stained are used, and individual-level cell analysis is performed. To this end, first, image stitching is performed for analysis of the same environment in units of the well plates, and uneven brightness due to the effects of illumination is adjusted based on the histogram. In order to automatically segment only the cell nucleus region, which is the region of interest, from the improved image, a superpixel-based segmentation technique is applied using the fluorescence expression level and morphological information. After extracting 242 types of features from the image through the segmented cell region information, only the features related to cell viability are selected through the ReliefF algorithm. The proposed method can be applied to cell image-based phenotypic screening to determine a patient's response to a drug.

• The KIPS Transactions:PartA
• /
• v.10A no.5
• /
• pp.425-432
• /
• 2003

This paper presents an EMR(Electronic Medical Record) chart for efficient PDA through the quad tree image rendering based on the mobile. Using the intermediate image space algorithm instead of the final one for volume rendering, we have solved the probems of th eholes coming from the point-to-point to mapping. The quad-tree based on the delta-tree efficiently represents volume expressions and results in higher compression effects. With the volume rendering, we can decrease the rendering time and get a higher quality and efficiency for PDA through image based rendering.

• Proceedings of the IEEK Conference
• /
• 2008.06a
• /
• pp.683-688
• /
• 2008

The emotional information processing is to simulate and recognize human sensibility, sensuality or emotion, to realize natural and harmonious human-machine interface. This paper proposes an emotion-based image retrieval method. In this method, user can choose a linguistic query among some emotional adjectives. Then the system shows some corresponding representative images that are pre-evaluated by experts. Again the user can select a representative one among the representative images to initiate traditional content-based image retrieval (CBIR). By this proposed method any CBIR can be easily expanded as emotion-based image retrieval. In CBIR of our system, we use several color and texture visual descriptors recommended by MPEG-7. We also propose a fuzzy similarity measure based on Choquet integral in the CBIR system. For the communication between system and user, a relevance feedback mechanism is used to represent human subjectivity in image retrieval. This can improve the performance of image retrieval, and also satisfy the user's individual preference.

• Journal of KIISE:Databases
• /
• v.30 no.2
• /
• pp.145-156
• /
• 2003

Most of the content-based image retrieval systems focuses on similarity-based retrieval of natural picture images by utilizing color. shape, and texture features. For the neuroscience image databases, we found that retrieving similar images based on global average features is meaningless to pathological researchers. To realize the practical content-based retrieval on images in neuroscience databases, it is essential to represent internal contents or semantics of images in detail. In this paper, we present how to represent image contents and their related concepts to support more useful retrieval on such images. We also describe the operational semantics to support these advanced retrievals by using object-oriented message path expressions. Our schemes are flexible and extensible, enabling users to incrementally add more semantics on image contents for more enhanced content searching.