• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.103-110
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• 2015

In this paper, we propose a deblurring method using 1/4 selective filter. Deblurring methods require a lot of processing time for deblurring. In order to enhance execution speed, we propose a novel 1/4 selective filter. The proposed 1/4 selective filter restores major edge, but it distorts minor edge and texture. To solve this problem, we apply 1/4 selective filter to restore major edge and DOG(Difference of Gaussian) filter to restore minor edge and texture. Experimental results show that the proposed method removes the blur effectively.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.625-631
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• 2010

This paper proposes lane recognition algorithm using lane prominence technique to extract lane candidate. The lane prominence technique is combined with embossing effect, lane thickness check, and lane extraction using mask. The proposed lane recognition algorithm consists of preprocessing, lane candidate extraction and lane recognition. First, preprocessing is executed, which includes gray image acquisition, inverse perspective transform and gaussian blur. Second, lane candidate is extracted by using lane prominence technique. Finally, lane is recognized by using hough transform and least square method. To evaluate the proposed lane recognition algorithm, this algorithm was applied to the detection of lanes in the rainy and night day. The experiment results showed that the proposed algorithm can recognize lane in various environment. It means that the algorithm can be applied to lane recognition to drive unmanned vehicles.

• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.264-267
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• 2015

본 논문에서는 개선된 고속의 Back Projection 기법과 에지맵 보간을 이용한 단일영상 기반의 초해상도(super resolution) 영상을 생성하는 알고리즘을 제안한다. 본 논문에서 제안하는 알고리즘은 영상의 색채 왜곡을 방지하기 위해 RGB 컬러 도메인에서 HSV 컬러 도메인으로 변경하여 밝기정보인 V만 이용한다. 먼저 잡음제거와 속도 향상을 위해 개선된 고속 back projection을 이용해 영상을 확대 재구성한다. 이와 함께 LoG(laplacian of gaussian) 필터링을 이용하여 에지 맵을 추출한다. 에지의 정보와 back projection의 결과를 이용하여 고해상도 영상을 재구성한다. 제안하는 알고리즘을 이용하여 복원한 영상은 부자연스러운 인공물을 효과적으로 제거하고, blur현상을 줄여 에지 정보를 보정하고 강조해준다. 또한 실험을 통해 제안하는 알고리즘이 기존의 보간법과 전통적인 back projection 결과보다 주관적인 화질이 우수하고 객관적으로 우수한 성능을 나타내는 것을 입증한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.637-639
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• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2369-2381
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• 1999

In this paper, we propose an iterative algorithm for reducing the blocking artifact in block transform-coded images by using a wavelet transform. In the proposed method, an image is considered as a set of one-dimensional horizontal and vertical signals and one-dimensional wavelet transform is utilized in which the mother wavelet is the first order derivative of a Gaussian like function. The blocking artifact is reduced by removing the blocking component, that causes the variance at the block boundary position in the first scale wavelet domain to be abnormally higher than those at the other positions, using a minimum mean square error (MMSE) filter in the wavelet domain. This filter minimizes the MSE between the ideal blocking component-free signal and the restored signal in the neighborhood of block boundaries in the wavelet domain. It also uses local variance in the wavelet domain for pixel adaptive processing. The filtering and the projection onto a convex set of quantization constraint are iteratively performed in alternating fashion. Experimental results show that the proposed method yields not only a PSNR improvement of about 0.56-1.07 dB, but also subjective quality nearly free of the blocking artifact and edge blur.

• Journal of Broadcast Engineering
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• v.18 no.1
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• pp.77-87
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• 2013

In this paper, we present a novel method for local image descriptor called exact order based descriptor (EOD) which is robust to illumination changes and Gaussian noise. Exact orders of image patch is induced by changing discrete intensity value into k-dimensional continuous vector to resolve the ambiguity of ordering for same intensity pixel value. EOD is generated from overall distribution of exact orders in the patch. The proposed local descriptor is compared with several state-of-the-art descriptors over a number of images. Experimental results show that the proposed method outperforms many state-of-the-art descriptors in the presence of illumination changes, blur and viewpoint change. Also, the proposed method can be used for many computer vision applications such as face recognition, texture recognition and image analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.22-27
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• 2014

Blocking and ringing artifacts continue to be the most serious defects that occur in images and video streams compressed to low bit rates using block-based discrete cosine transform(DCT) compression standards. These artifacts contain the high frequency components near the block and the edge boundaries. Usually the lowpass filter can remove them. However, simple lowpass filter results into blur by removing important information such as edges at the same time. To overcome these problems, we propose a novel postfiltering algorithm that calculate the weight value based on the intensity similarity in the neighboring pixels and multiply this weight to the Gaussian lowpass filter coefficient. Experimental results show that the proposed technique provides satisfactory performance in both objective and subjective image quality.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.103-108
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• 2012

Recently, as the prevalence of high-performance mobile devices and the application of the multimedia content are expanded, Super Resolution (SR) technique which reconstructs low resolution images to high resolution images is becoming important. And in the mobile devices, the development of the SR algorithm considering the operation quantity or memory is required because of using the restricted resources. In this paper, we propose a new single frame fast SR technique suitable for mobile devices. In order to prevent color distortion, we change RGB color domain to HSV color domain and process the brightness information V (Value) considering the characteristics of human visual perception. First, the low resolution image is enlarged by the improved fast back projection considering the noise elimination. And at the same time, the reliable edge map is extracted by using the LoG (Laplacian of Gaussian) filtering. Finally, the high definition picture is reconstructed by using the edge information and the improved back projection result. The proposed technique removes effectually the unnatural artefact which is generated during the super resolution restoration, and the edge information which can be lost is amended and emphasized. The experimental results indicate that the proposed algorithm provides better performance than conventional back projection and interpolation methods.