• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.628-638
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• 1999

In this paper, we presents a method of retrieving 24 bpp RGB images based on color-spatial features. For each image, it is subdivided into regions by using similarity of color after converting RGB color space to CIE L*u*v* color space that is perceptually uniform. Our segmentation algorithm constrains the size of region because a small region is discardable and a large region is difficult to extract spatial feature. For each region, averaging color and center of region are extracted to construct color-spatial features. During the image retrieval process, the color and spatial features of query are compared with those of the database images using our similarity measure to determine the set of candidate images to be retrieved. We implement a content-based color image retrieval system using the proposed method. The system is able to retrieve images by user graphic or example image query. Experimental results show that Recall/Precision is 0.80/0.84.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1679-1689
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• 2016

Recently, due to the rapid development of multimedia technologies, as image data has been extensive and large-scaled, the problem of increasing the time needed to retrieve the desired image is gradually critical. Image retrieval system that allows users to quickly and accurately search for the desired image information has been researched for a long time. However, in the case of content-based image retrieval representative Color Histogram, Color Coherence Vectors (CCV), Scale Invariant Feature Transform (SIFT) used in sensitive to changes in brightness, rotation, there is a problem that can occur misrecognized division off the power. In this paper, in order to evaluate the video retrieval system proposed, no change in brightness, respectively 0°, 90°, 180°, 270° rotated brightness up based on the case of changing, when the brightness down the results were compared with the performance evaluation of the system is an average of about 2% to provide the difference in performance due to changes in brightness, color histogram is an average of about 12.5%, CCV is an average of about 12.25%, it appeared in the SIFT is an average of about 8.5%, Thus, the proposed system of the variation width of the smallest in average about 2%, was confirmed to be robust to changes in the brightness and rotation than the existing systems.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.1-10
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• 2005

Content-based image retrieval systems are being actively investigated owing to their ability to retrieve images based on the actual visual content rather than by manually associated textual descriptions. In this paper, we propose a novel approach for image retrieval based on edge structural features using edge correlogram and color coherence vector. After color vector angle is applied in the pre-processing stage, an image is divided into two image parts (high frequency image and low frequency image). In low frequency image, the global color distribution of smooth pixels is extracted by color coherence vector, thereby incorporating spatial information into the proposed color descriptor. Meanwhile, in high frequency image, the distribution of the gray pairs at an edge is extracted by edge correlogram. Since the proposed algorithm includes the spatial and edge information between colors, it can robustly reduce the effect of the significant change in appearance and shape in image analysis. The proposed method provides a simple and flexible description for the image with complex scene in terms of structural features of the image contents. Experimental evidence suggests that our algorithm outperforms the recently histogram refinement methods for image indexing and retrieval. To index the multidimensional feature vectors, we use R*-tree structure.

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.51-55
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• 2017

In this paper, we designed a LBS-based smart platform for Lifelog service that can utilize the other's lifelog information. The conventional Lifelog service means that the system records the daily activities of the smart device user so the user can retrieve the early-recorded information later. The proposed Lifelog service platform uses the GPS/UFID location information and the various information extracted from the image as the lifelog data. Further, the proposed Lifelog platform using DB can provide the user with the Lifelog data recorded by the other service user. The system usually provide the other's Lifelog data within the 500m distance from the user and the range of distance can be adjustable. The proposed smart platform based on image recognition for Lifelog can acquire the image from the smart device directly and perform the various image recognition processing to produce the useful image attributes. And it can store the location information, image data, image attributes and the relevant web informations on the database that can be retrieved by the other use's request. The attributes stored and managed in the image information database consist of the followings: Object ID, the image type, the capture time and the image GPS coordinates. The image type attribute has the following values: the mountain, the sea, the street, the front of building, the inside of building and the portrait. The captured image can be classified into the above image type by the pattern matching image processing techniques and the user's direct selection as well. In case of the portrait-attribute, we can choose the multiple sub-attribute values from the shirt, pant, dress and accessory sub-attributes. Managing the Lifelog data in the database, the system can provide the user with the useful additional services like a path finding to the location of the other service user's Lifelog data and information.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.965-976
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• 2020

We present in this work a segmentation method of E. coli bacterial images generated via phase contrast microscopy using a deep learning based hybrid feature generation. Unlike conventional machine learning methods that use the hand-crafted features, we adopt the denoising autoencoder in order to generate a precise and accurate representation of the pixels. We first construct a hybrid vector that combines original image, difference of Gaussians and image gradients. The created hybrid features are then given to a deep autoencoder that learns the pixels' internal dependencies and the cells' shape and boundary information. The latent representations learned by the autoencoder are used as the inputs of a softmax classification layer and the direct outputs from the classifier represent the coarse segmentation mask. Finally, the classifier's outputs are used as prior information for a graph partitioning based fine segmentation. We demonstrate that the proposed hybrid vector representation manages to preserve the global shape and boundary information of the cells, allowing to retrieve the majority of the cellular patterns without the need of any post-processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.856-873
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• 2011

Reversible watermarking is an open problem in information hiding field, with embedding the encoded bit '1' or '0' into some sensitive images, such as the law enforcement, medical records and military images. The technique can retrieve the original image without distortion, after the embedded message has been extracted. Histogram-based scheme is a remarkable breakthrough in reversible watermarking schemes, in terms of high embedding capacity and low distortion. This scheme is lack of capacity control due to the requirement for embedding large-scale data, because the largest hidden capacity is decided by the amount of pixels with the peak point. In this paper, we propose a reversible watermarking scheme to enlarge the number of pixels with the peak point as large as possible. This algorithm is based on an adaptive edge-guided interpolation, furthermore, hides messages by interpolation-error, i.e. the difference between the original and interpolated image value. Simulation results compared with other state-of-the-art reversible watermarking schemes in this paper demonstrate the validity of the proposed algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.514-519
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• 1992

To make an accurate retrieval of the proportion of each category among mixed pixels (Mixel's) of a remotely sensed imagery, a maximum likelihood estimation method of category proportion is proposed. In this method, the observed multispectral vector is considered as probability variables along with the approximation that the supervised data of each category can be characterized by normal distribution. The results show that this method can retrieve accurate proportion of each category among Mixel's. And a index that can estimate the degree of error in each category is proposed. AS one of the application of the proportion estimation, a method for image classification based on category proportion estimation is proposed. In this method all pixel in a remotely sensed imagery are assumed to be Mixel's, and are classified to most dominant category. Among the Mixel's, there exists unconfidential pixels which should be categorized as unclassified pixels. In order to discriminate them, two types of criteria, Chi square and AIC, are proposed for fitness test on pure pixel hypothesis. Experimental result with a simulated dataset show an usefulness of proposed classification criterion compared to the conventional maximum likelihood criterion and applicability of the fitness tests based on Chi square and AIC,

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.9
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• pp.781-786
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• 2013

Multiplexing information over parallel data channels based on RF MIMO concept is possible to achieve considerable data rates over large transmission ranges with just a single transmitting element. Visual multiplexing MIMO techniques will send independent streams of bits using the multiple elements of the light transmitter array and recording over a group of camera pixels can further enhance the data rates. The proposed system is a combination of the reliance on computer vision algorithms for tracking and OOK cell frame modulation. LED array are controlled to transmit message in the form of digital information using ON-OFF signaling with ON-OFF pulses (ON = bit 1, OFF = bit 0). A camera captures image frames of the array which are then individually processed and sequentially decoded to retrieve data. To demodulated data transmission, a motion tracking algorithm is implemented in OpenCV (Open source Computer Vision library) to classify the transmission pattern. One of the most advantages of proposed architecture is Computer Vision (CV) based image analysis techniques which can be used to spatially separate signals and remove interferences from ambient light. It will be the future challenges and opportunities for mobile communication networking research.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.603-614
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• 1999

As multimedia application services on high-speed information network have been rapidly developed, the need for the video information management system that provides an efficient way for users to retrieve video data is growing. In this paper, we propose a video data model that integrates free annotations, image features, and spatial-temporal features for video purpose of improving content-based retrieval of video data. The proposed video data model can act as a generic video data model for multimedia applications, and support free annotations, image features, spatial-temporal features, and structure information of video data within the same framework. We also propose the video query language for efficiently providing query specification to access video clips in the video data. It can formalize various kinds of queries based on the video contents. Finally we design and implement the query processing engine for efficient video data retrieval on the proposed metadata model and the proposed video query language.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3249-3252
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• 1999

In this paper, we present the Tele-PACS of radiology, which uses the communication network as asymetric satellite data communication system. The asymetric satellite data communication system uses receive-only satellite links for data delivery and PSTN(Public Switched Telephone Network) modem or N-ISDN(Integrate Services Digital Network) for communication. The satellite communication linking shows the very high-speed performance than terrestial linking such as 28.8 kbps modem linking and 56Kbps linking. The satellite linking is 5 - 10 times faster than the 56Kbps linking. We conclude that 1) Satellite networking is currently the cheapest and fastest solution for internet access. 2) Web-based Image-Viewer enables small size hospitals in rural area to connect to central PACS easily and to retrieve the image data reliably. 3) The suggested teleradiology system using satellite networking could be adequate to fast telemedicine and telecare for rural hospitals especially located in geographically isolated areas such as islands.