• Journal of Broadcast Engineering
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• v.5 no.2
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• pp.239-246
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• 2000

An efficient control parameter extraction scheme required for auto-focusing control of a stereo camera is proposed. Without loss of generality, it is assumed that an interesting object exists in the center of a captured image by a stereo camera. In such a case. we apply a 2-dimensional wavelet transform to the center area with specific image size in the captured image. Next, we extract required focus control parameters using an Ll-norm for doubly high-pass filtered components. Experimental results show that the proposed scheme is effectively applicable to the auto-focusing for a stereo camera compared to the conventional control scheme using discrete cosine transform (DCT).

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.614-621
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• 2018

This paper proposes a method of restoring corrupted depth image captured by depth camera through unsupervised learning using generative adversarial network (GAN). The proposed method generates restored face depth images using 3D morphable model convolutional neural network (3DMM CNN) with large-scale CelebFaces Attribute (CelebA) and FaceWarehouse dataset for training deep convolutional generative adversarial network (DCGAN). The generator and discriminator equip with Wasserstein distance for loss function by utilizing minimax game. Then the DCGAN restore the loss of captured facial depth images by performing another learning procedure using trained generator and new loss function.

• The Journal of the Korea Contents Association
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• v.15 no.11
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• pp.18-26
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• 2015

Geometric distortion and shadow effect due to capturing angle could be included in document copy images that are captured by a camera in stead of a scanner. In this paper, a clean black and white document image generation algorithm by distortion correction and shadow elimination based on a camera, is proposed. In order to correct geometric distortion such as straightening un-straight boundary lines occurred by camera lens radial distortion and eliminating outlying area included by camera direction, second derivative filter based document boundary detection method is developed. Black and white images have been generated by adaptive binarization method by eliminating shadow effect. Experimental results of the black and white document image generation algorithm by recovering geometrical distortion and eliminating shadow effect for the document images captured by smart phone camera, shows very good processing results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.1103-1106
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• 2005

The purpose of this research is design of Vision Box which can capture an image which inputs through the camera and understand movement of object included in captured image. In design, we tried to satisfy user's requirements. We made Vision Box can analyze movement of object in image captured by camera without additional instruments. In addition, it is possible that communicate with PLC and operate Vision Box by remote control. We could verify the Vision Box capability by using it to automobile engine pattern analysis. We expect the Vision Box will be used various industrial fields.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.19-23
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• 2021

A statistical approach to inspection of the 3-D shape of micro solder balls is proposed, where an optical method with spatially arranged LED and specular reflection is used. The reflected image captured by a vision system was analyzed to calculate the relative displacements of LED's in the image. Also, the statistics of displacements for the solder balls contained in a captured image are used to detect existing defects, and the usefulness of the proposed method is shown via experiments.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.3
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• pp.62-66
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• 2024

A statistical approach to inspection of the 3-D shape of micro solder balls is proposed, where an optical method with spatially arranged LED and specular reflection is used. The reflected image captured by a vision system was analyzed to calculate the relative displacements of LED's in the image. Also, the statistics of displacements for the micro solder balls contained in a captured image are used to detect existing defects, and the usefulness of the proposed method is shown via experiments.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.79-82
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• 2009

In this paper, we propose new image processing method to detect fire image. At captured image from camera, we using OpenCV library to implement various image processing techniques such like differential image, binarization image, contour extraction, remove noise(morphology open, close), pixel calculation, flickering extraction, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5039-5055
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• 2018

The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.926-930
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• 2006

Current image retrieval techniques have shortcomings that make it difficult to search for images based on a semantic understanding of what the image is about. Since an image is normally associated with multiple contexts (e.g. when and where a picture was taken,) the knowledge of these contexts can enhance the quantity of semantic understanding of an image. In this paper, we present a context-aware image retrieval system, which uses the context information to infer a kind of metadata for the captured images as well as images in different collections and databases. Experimental results show that using these kinds of information can not only significantly increase the retrieval accuracy in conventional content-based image retrieval systems but decrease the problems arise by manual annotation in text-based image retrieval systems as well.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.3
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• pp.153-163
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• 2016

Local feature extraction methods for images and videos are widely applied in the fields of image understanding and computer vision. However, robust features are detected differently when using the latest feature detectors and descriptors because of diverse image environments. This paper analyzes various feature extraction methods by summarizing algorithms, specifying properties, and comparing performance. We analyze eight feature extraction methods. The performance of feature extraction in various image environments is compared and evaluated. As a result, the feature detectors and descriptors can be used adaptively for image sequences captured under various image environments. Also, the evaluation of feature detectors and descriptors can be applied to driving assistance systems, closed circuit televisions (CCTVs), robot vision, etc.