• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.2
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• pp.188-194
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• 2010

In this paper, the typical Synthetic Aperture Radar (SAR) image quality parameters and analysis method are defined, and the SAR image analysis tool is presented for SAR image evaluation. The structure of the developed SAR image analysis tool consists of four key modules; point target analysis (PTA) module, distributed target analysis (DTA) module, ambiguity analysis (AMA) module, and NESZ analysis (NESZA) module. The developed tool is able to extract the various SAR system parameters from standard SAR product format files. Based on these extracted system parameters, typical SAR image quality parameters are derived from SAR image data.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.7
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• pp.498-506
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• 2003

A computer vision system applied to an intelligent safety vehicle has been required to be worked on a small sized real time special purposed hardware not on a general purposed computer. In addition, the system should have a high reliability even under the adverse road traffic environment. This paper presents a design and an implementation of an onboard hardware system taking into account for high speed image processing to analyze a road traffic scene. The system is mainly composed of two parts: an early processing module of FPGA and a postprocessing module of DSP. The early processing module is designed to extract several image primitives such as the intensity of a gray level image and edge attributes in a real-time Especially, the module is optimized for the Sobel edge operation. The postprocessing module of DSP utilizes the image features from the early processing module for making image understanding or image analysis of a road traffic scene. The performance of the proposed system is evaluated by an experiment of a lane-related information extraction. The experiment shows the successful results of image processing speed of twenty-five frames of 320$\times$240 pixels per second.

• Smart Media Journal
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• v.3 no.1
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• pp.16-21
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• 2014

The demand for food rises proportionally as population grows. To be able to achieve sustainable supply of livestock products, efficient farm management is a necessity. With the advancement in technology it also brought innovations that could be harness in order to achieve better productivity in animal production and agriculture. Precision Livestock Farming (PLF) is a budding concept of making use of smart sensors or available devices to automatically and continuously monitor and manage livestock production. With this concept, this paper introduces a swine management system that integrates image processing technique for weight monitoring. This system captures pig images using camera, evaluate and estimate the weight base on the captured image. It is comprised of Pig Module, Breeding Module, Health and Medication Module, Weighr Module, Data Analysis Module and Report Module to help swine farm administrators better understand the performance and situation of the swine farm. This paper aims to improve the management in both small and big livestock raisers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2511-2519
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• 2009

In this paper, we introduce the methodological system design via feature selection using Principal Component Analysis and Particle Swarm Optimization algorithms. The overall methodological system design comes from three kinds of modules such as preprocessing module, feature extraction module, and recognition module. First, Histogram equalization enhance the quality of image by exploiting contrast effect based on the normalized function generated from histogram distribution values of 2D face image. Secondly, PCA extracts feature vectors to be used for face recognition by using eigenvalues and eigenvectors obtained from covariance matrix. Finally the feature selection for face recognition among the entire feature vectors is considered by means of the Particle Swarm Optimization. The optimized Polynomial-based Radial Basis Function Neural Networks are used to evaluate the face recognition performance. This study shows that the proposed methodological system design is effective to the analysis of preferred face recognition.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.509-511
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• 2004

This paper outlines the development of image processing system, which will allow the general users in Government and Public organizations easily to use and apply KOMPSAT EOC images in their own business. The system includes an import/export module of EOC image distributed in Hierarchical Data Format (HDF) file and various image processing analysis modules. Especially, the image mosaic and subset functions are designed to use EOC image as an image map, generating the Ortho-image module. To update the various spatial data with EOC image, some essential modules such as change detection by pattern recognition, overlay between images and vector data, and modification of vector data are implemented in the system. The system is developed based on the user request analysis of government agency, and suited for more efficient use of satellite image in public applications. Such system is expected to contribute to practical application of KOMPSAT-2 that will be launched in 2005. Further efforts will be made to accommodate the KOMPSAT -2 MSC data.

• Transactions of the Society of Information Storage Systems
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• v.7 no.2
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• pp.70-74
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• 2011

The mobile camera module is a device to be inserted in the digital device for camera feature. The mobile camera module is being shaken by vibrations such as handshake during the exposure time. The clarity is compromised by these vibrations, thus the vibration is considered as an external disturbance. Moreover the use of mobile camera module has been being expanded for automotive vibration should be considered. These external disturbances can cause image blurring, thus optical image stabilization should be applied for image compensation. The compensator is fulfilled mechanically by movable lens group or image sensor that adjusts the optical path to the camera movement. Open loop control is useful for well-defined systems like compliant mechanism. Notch filter and lead compensator are designed and applied to improve the stability and bandwidth. The final level of image compensating is confirmed by image processing with MATLAB and CODE V to verify the better performance.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.05a
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• pp.79-80
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• 2011

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2552-2570
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• 2022

Underwater images usually have various problems, such as the color cast of underwater images due to the attenuation of different lights in water, the darkness of image caused by the lack of light underwater, and the haze effect of underwater images because of the scattering of light. To address the above problems, the channel attention mechanism, strengthen-operate-subtract (SOS) boosting mechanism and gated fusion module are introduced in our paper, based on which, an underwater image recovery network is proposed. First, for the color cast problem of underwater images, the channel attention mechanism is incorporated in our model, which can well alleviate the color cast of underwater images. Second, as for the darkness of underwater images, the similarity between the target underwater image after dehazing and color correcting, and the image output by our model is used as the loss function, so as to increase the brightness of the underwater image. Finally, we employ the SOS boosting module to eliminate the haze effect of underwater images. Moreover, experiments were carried out to evaluate the performance of our model. The qualitative analysis results show that our method can be applied to effectively recover the underwater images, which outperformed most methods for comparison according to various criteria in the quantitative analysis.

• Journal of Korea Multimedia Society
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• v.9 no.9
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• pp.1139-1149
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• 2006

This paper describes a novel and efficient algorithm, which extracts focused objects from still images with low depth-of-field (DOF). The algorithm unfolds into four modules. In the first module, a HOS map, in which the spatial distribution of the high-frequency components is represented, is obtained from an input low DOF image [1]. The second module finds OOI candidate by using characteristics of the HOS. Since it is possible to contain some holes in the region, the third module detects and fills them. In order to obtain an OOI, the last module gets rid of background pixels in the OOI candidate. The experimental results show that the proposed method is highly useful in various applications, such as image indexing for content-based retrieval from huge amounts of image database, image analysis for digital cameras, and video analysis for virtual reality, immersive video system, photo-realistic video scene generation and video indexing system.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.6
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• pp.447-452
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• 2011

In this study, the polymeric membrane module is used as a diffuser and an image analysis technique based on visual information is applied to get bubble characteristics. The bubble size generated passed through polymeric membrane module was smaller from 30 to 64% than that of air stone, and bubble volume over 70% was ranged from 0.2 to 0.82 mm. But over 80% the bubbles from air stone diffuser ranged from 0.77 to 1.08 mm. The air stone and polymeric membrane module used as diffuser for a flotation system. The floc size inside the flotation reactor using air stone diffuser was bigger than that of the polymeric membrane module, which means that the micro-bubbles generated from polymeric membrane module could provide better opportunities for collisions between colloidal particles than those from air stone diffuser. Therefore, there is a possibility to apply the polymeric membrane module as a diffuser to increase the removal efficiency in the flotation process. Also, the image analysis technique used in this study could be applied as a useful analytical tool for acquisition of an information about the bubble characteristic.