• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.253-260
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• 1999

In this paper, we suggest a new direct method for mage segmentation using texture and color information combined through a multivariate linear discriminant algorithm. The color texture is computed in nin 3${\times}$3 masks obtained from each 3${\times}$3${\times}$3 spatio-spectral neighborhood in the image using the classical haralick and Pressman texture features. Among these 9${\times}$28 texture features the best set was extracted from a training set. The resulting set of 10 features were used to segment an image into four different regions. The resulting segmentation was Compared to classical color and texture segmentation methods using both box classifiers and maximum likelihood classification. It compared favourably on the test image from a Fastred-Lightgreen stained prostatic histological tissue section based on visual inspection. The classification accuracy of 97.5% for the new method obtained on the training data was also among the best of the tested methods. If these results hold for a larger set of images, this method should be a useful tool for segmenting images where both color and texture are relevant for the segmentation process.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.367-370
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• 2015

This paper proposes an improve method of the detection performance of traffic lights for autonomous driving cars. Earlier detection methods used to adopt color thresholding, template matching and based learning maching methods, but its have some problems such as recognition rate decreasing, slow processing time. The proposed method uses both detection mask and morphological preprocessing. Firstly, input color images are converted to YCbCr image in order to strengthen its illumination, and horizontal edge components are extracted in the Y Channel. Secondly, the region of interest is detected according to morphological characteristics of the traffic lights. Finally, the traffic signal is detected based on color distributions. The proposed method showed that the detection rate and processing time improved rather than the conventional algorithm about some surrounding environments.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2555-2564
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• 2000

In this paper, a new unsupervised image segmentation algorithm is proposed. To model the contextual information presented in images, the characteristics of the Markov random fields (MRF) are utilized. Textured images are modeled as realizations of the stationary Gaussian MRF on a two-dimensional square lattice using the conditional autoregressive (CAR) equations with a second-order noncausal neighborhood. To detect boundaries, hypothesis tests over two masked areas are performed. Under the hypothesis, masked areas are assumed to belong to the same class of textures and CAR equation parameters are estimated in a minimum-mean-square-error (MMSE) sense. If the hypothesis is rejected, a measure of dissimilarity between two areas is accumulated on the rejected area. This approach produces potential edge maps. Using these maps, boundary detection can be performed, which resulting no micro edges. The performance of the proposed algorithm is evaluated by some experiments using real images as weB as synthetic ones. The experiments demonstrate that the proposed algorithm can produce satisfactorY segmentation without any a priori information.

• Journal of the Korean earth science society
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• v.26 no.1
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• pp.58-65
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• 2005

Homomorphic filtering improves image by enhancing high components and reducing low components in the Sequency domain based on FFT, as one of useful digital image processing techniques. In this study, the application program f3r homomorphic filtering was developed. Using this program, satellite imageries and geophysical image such as magnetic image data were processed and their results were analyzed. In case of applying to other techniques suck as histogram equalization and kernel-based masking f3r the same purpose. they often cause the slight distortion of boundary or overall change of brightness values on the whole image. Whereas. homomorphic filtering has ability to enhance selectively detailed components in a target image. Therefore. this technique can be effectively used for extraction or separation of complex types of characteristics contained in the satellite imagery. In addition, this technique would be applicable to investigate anomalous zone in various geophysical image data.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.43-48
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• 2011

Among various methods proposed earlier, fuzzy image filtering is usually one of the favored techniques because it has less blurring effect and the decrease of noise removal rate after filtering. However, fuzzy filtering is ineffective on color images since it is firstly developed with gray scale. Thus, in this paper, we propose a fuzzy filtering algorithm for color images. First, we divide RGB color information from image into three channels of R, G, and B and judge the possibility of each pixel with mask by fuzzy logic independently. The output pixel value might be the average or median according to the degree of noise. Our experiment successfully verifies the effectiveness of new algorithm in color image.

• Journal of IKEEE
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• v.19 no.1
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• pp.10-17
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• 2015

In this Paper, an efficient method of FPGA based design and implementation of Sobel Edge detector block using 3-Line buffers is presented. The FPGA provides the proper and sufficient hardware for image processing algorithms with flexibility to support Sobel edge detection algorithm. A pipe-lined method is used to implement the edge detector. The proposed Sobel edge detection operator is an model using of Finite State Machine(FSM) which executes a matrix mask operation to determine the level of edge intensity through different of pixels on an image. This approach is useful to improve the system performance by taking advantage of efficient look up tables, flip-flop resources on target device. The proposed Sobel detector using 3-line buffers is synthesized with Xilinx ISE 14.2 and implemented on Virtex II xc2vp-30-7-FF896 FPGA device. Using matlab, we show better PSNR performance of proposed design in terms of 3-Line buffers utilization.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.233-238
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• 2005

With iris recognition algorithm, unique iris code can be generated and user can be identified by using iris pattern. However, if unnecessary information such as eyelash is included in iris region, the error for iris recognition is increased, consequently. In detail, if iris region is used to generate ins code not excluding eyelash and the position of eyelash is moved, the iris codes are also changed and the error rate is increased. To overcome such problem, we propose the method of detecting eyelash by using mask and excluding the detected eyelash region in case of generating iris code. Experimental results show that EER(Equal Error Rate) for iris recognition using the proposed algorithm is lessened as much as $0.18\%$ compared to that not using it.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.543-552
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• 2005

This paper proposes the extraction of coronary arteries based on DSA(Digital Subtraction Angiography) through a texture analysis of background in the angiography. DSA is a well established modality for the visualization of coronary arteries. DSA involves the subtraction of a mask image - an image of the heart before injection of contrast medium - from live image. However, this technique is sensitive to the movement of background and can result to a wrong detection by the variance of background gray-level intensity between two images. Therefore, this paper solves a structural problem resulted from a background movement bV selecting an image which has the least difference of movement through an analysis of the similarity of background texture and proposes a method to extract only the blood vessel efficiently through local gray-level correction of the selected image. Using the coronary angiogram of 5 patients clinical data, we proved that the proposed method has the lower false-detection rate, approximately $2\%$, and the higher accuracy than the existing methods.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.127-136
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• 2008

A digitized image passes by encoding, storing or transmitting to show it to users. In this process, may be users would want to see a specific region of the image. And depending on the system features or in the case that the resolution of the image is large, it will take a huge time that the image show to the users. In this time, it will be resonable that the part users want to see shows earlier and afterward the other parts show. For this, JPEG2000 standards provide ROI. Although ROI extraction that users specify ROI arbitrarily is the best, people not always participate in doing all the images. There needs an automatic ROI extracting and storing in some images. JPEG2000 should extract and send an ROI automatically when the images is encoded without ROI. This study proposes a method that automatically extracts an ROI, makes the ROI masks, transfers the masked image preferentially and the background. And the study compares and experiments the proposed method and the method not having ROI.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.249-255
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• 2004

In fingerprint verification and identification, fingerprint and background region should be segmented. For this purpose, most systems obtain variance of brightness of X and Y direction using Sobel mask. To decide given local region is background or not, the variance is compared with a certain threshold. Although this method is simple, most fingerprint image does not separated with two region of fingerprint and background region. In this paper, we presented a new segmentation algorithm based on Run-Length Connectivity analysis. For a given binary image after thresholding, suggested algorithm calculates RL of X and Y direction. Until the given image is segmented to two regions, small run region is successively inverted. Experimental result show that this algorithm effectively separates fingerprint region and background region.