• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.479-482
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• 2003

Edge, detected from image processing includes variety of information about original image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now. And with the recent progress of wavelet theory which is presented as a new technique of signal processing fields, wavelet transform is being applied to many fields which analyzes singularities of image. For this reason, this paper detected original image's edge from the information such as local maximum, direction, and location of the wavelet transform data by using wavelet function which is independent of width of line.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• Journal of the Korea Society of Computer and Information
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• v.16 no.6
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• pp.71-77
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• 2011

In this paper, we propose a learning based super resolution algorithm using local block for image enhancement of vehicle license plate. Local block is defined as the minimum measure of block size containing the associative information in the image. Proposed method essentially generates appropriate local block sets suitable for various imaging conditions. In particular, local block training set is first constructed as ordered pair between high resolution local block and low resolution local block. We then generate low resolution local block training set of various size and blur conditions for matching to all possible blur condition of vehicle license plates. Finally, we perform association and merging of information to reconstruct into enhanced form of image from training local block sets. Representative experiments demonstrate the effectiveness of the proposed algorithm.

• Journal of Information Processing Systems
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• v.12 no.4
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• pp.631-643
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• 2016

Due to the block-based discrete cosine transform (BDCT), JPEG compressed images usually exhibit blocking artifacts. When the bit rates are very low, blocking artifacts will seriously affect the image's visual quality. A bilateral filter has the features for edge-preserving when it smooths images, so we propose an adaptive-weighted bilateral filter based on the features. In this paper, an image-deblocking scheme using this kind of adaptive-weighted bilateral filter is proposed to remove and reduce blocking artifacts. Two parameters of the proposed adaptive-weighted bilateral filter are adaptive-weighted so that it can avoid over-blurring unsmooth regions while eliminating blocking artifacts in smooth regions. This is achieved in two aspects: by using local entropy to control the level of filtering of each single pixel point within the image, and by using an improved blind image quality assessment (BIQA) to control the strength of filtering different images whose blocking artifacts are different. It is proved by our experimental results that our proposed image-deblocking scheme provides good performance on eliminating blocking artifacts and can avoid the over-blurring of unsmooth regions.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.10-21
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• 2016

Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.796-804
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• 2002

This paper presents a new algorithm of fingerprint image analysis and processing using directional filter bank(DFB). The directional components of ridge is very important in pre-processing steps of fingerprint image processing such as image enhancement by directional filtering followed by estimationg the directional image of ridge patterns. The DFB analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint processing algorithm using the DFB is proposed. The algorithm decomposes the fingerprint image into directional subband images and performs directional map generation, foreground segmentation, singular points extraction and image enhancement based on local directional energy estimate.

• Korean Journal of Remote Sensing
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• v.36 no.4
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• pp.545-555
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• 2020

This paper focuses on automatic image registration between EO (Electro-Optical) and IR (InfraRed) satellite images with different spectral properties using block-based approach and simple preprocessing technique to enhance the performance of feature matching. If unpreprocessed EO and IR images from Kompsat-3A satellite were applied to local feature matching algorithms(Scale Invariant Feature Transform, Speed-Up Robust Feature, etc.), image registration algorithm generally failed because of few detected feature points or mismatched pairs despite of many detected feature points. In this paper, we proposed a new image registration method which improved the performance of feature matching with block-based registration process on 9-divided image and pre-processing technique based on adaptive histogram equalization. The proposed method showed better performance than without our proposed technique on visual inspection and I-RMSE. This study can be used for automatic image registration between various images acquired from different sensors.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.417-426
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• 2023

To improve the effect of image restoration and solve the image detail loss, an image dehazing enhancement algorithm based on mean guided filtering is proposed. The superpixel calculation method is used to pre-segment the original foggy image to obtain different sub-regions. The Ncut algorithm is used to segment the original image, and it outputs the segmented image until there is no more region merging in the image. By means of the mean-guided filtering method, the minimum value is selected as the value of the current pixel point in the local small block of the dark image, and the dark primary color image is obtained, and its transmittance is calculated to obtain the image edge detection result. According to the prior law of dark channel, a classic image dehazing enhancement model is established, and the model is combined with a median filter with low computational complexity to denoise the image in real time and maintain the jump of the mutation area to achieve image dehazing enhancement. The experimental results show that the image dehazing and enhancement effect of the proposed algorithm has obvious advantages, can retain a large amount of image detail information, and the values of information entropy, peak signal-to-noise ratio, and structural similarity are high. The research innovatively combines a variety of methods to achieve image dehazing and improve the quality effect. Through segmentation, filtering, denoising and other operations, the image quality is effectively improved, which provides an important reference for the improvement of image processing technology.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.385-399
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• 2017

Nowadays, with the development of signal processing technique, the protection to the integrity and authenticity of images has become a topic of great concern. A blind image authentication technology with high tamper detection accuracy for different common attacks is urgently needed. In this paper, an improved fragile watermarking method based on local binary pattern (LBP) is presented for blind tamper location in images. In this method, a binary watermark is generated by LBP operator which is often utilized in face identification and texture analysis. In order to guarantee the safety of the proposed algorithm, Arnold transform and logistic map are used to scramble the authentication watermark. Then, the least significant bits (LSBs) of original pixels are substituted by the encrypted watermark. Since the authentication data is constructed from the image itself, no original image is needed in tamper detection. The LBP map of watermarked image is compared to the extracted authentication data to determine whether it is tampered or not. In comparison with other state-of-the-art schemes, various experiments prove that the proposed algorithm achieves better performance in forgery detection and location for baleful attacks.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.5 no.2
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• pp.57-62
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• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.