• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3312-3327
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• 2020

Plant diseases are a significant yield and quality constraint for farmers around the world due to their severe impact on agricultural productivity. Such losses can have a substantial impact on the economy which causes a reduction in farmer's income and higher prices for consumers. Further, it may also result in a severe shortage of food ensuing violent hunger and starvation, especially, in less-developed countries where access to disease prevention methods is limited. This research presents an investigation of Directional Local Quinary Patterns (DLQP) as a feature descriptor for plants leaf disease detection and Support Vector Machine (SVM) as a classifier. The DLQP as a feature descriptor is specifically the first time being used for disease detection in horticulture. DLQP provides directional edge information attending the reference pixel with its neighboring pixel value by involving computation of their grey-level difference based on quinary value (-2, -1, 0, 1, 2) in 0°, 45°, 90°, and 135° directions of selected window of plant leaf image. To assess the robustness of DLQP as a texture descriptor we used a research-oriented Plant Village dataset of Tomato plant (3,900 leaf images) comprising of 6 diseased classes, Potato plant (1,526 leaf images) and Apple plant (2,600 leaf images) comprising of 3 diseased classes. The accuracies of 95.6%, 96.2% and 97.8% for the above-mentioned crops, respectively, were achieved which are higher in comparison with classification on the same dataset using other standard feature descriptors like Local Binary Pattern (LBP) and Local Ternary Patterns (LTP). Further, the effectiveness of the proposed method is proven by comparing it with existing algorithms for plant disease phenotyping.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.55-67
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• 1998

This paper presents an automatic facial feature point extraction algorithm in sequential color images. To extract facial region in the video sequence, a moving color detection technique is proposed that emphasize moving skin color region by applying motion detection algorithm on the skin-color transformed images. The threshold value for the pixel difference detection is also decided according to the transformed pixel value that represents the probability of the desired color information. Eye candidate regions are selected using both of the black/white color information inside the skin-color region and the valley information of the moving skin region detected using morphological operators. Eye region is finally decided by the geometrical relationship of the eyes and color histogram. To decide the exact feature points, the PCA(Principal Component Analysis) is used on each eye and mouth regions. Experimental results show that the feature points of eye and mouth can be obtained correctly irrespective of background, direction and size of face.

• Journal of Radiation Protection and Research
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• v.43 no.3
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• pp.97-106
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• 2018

Background: A cargo container scanner using a high-energy X-ray generates a fan beam X-ray to acquire a transmitted image. Because the generated X-rays by LINAC may affect the image quality and radiation protection of the system, it is necessary to acquire accurate information about the generated X-ray beam distribution. In this paper, a diode-based multi-channel spatial dose measuring device for measuring the X-ray dose distribution developed for measuring the high energy X-ray beam distribution of the container scanner is described. Materials and Methods: The developed high-energy X-ray spatial dose distribution measuring device can measure the spatial distribution of X-rays using 128 diode-based X-ray sensors. And precise measurement of the beam distribution is possible through automatic positioning in the vertical and horizontal directions. The response characteristics of the measurement system were evaluated by comparing the signal gain difference of each pixel, response linearity according to X-ray incident dose change, evaluation of resolution, and measurement of two-dimensional spatial beam distribution. Results and Discussion: As a result, it was found that the difference between the maximum value and the minimum value of the response signal according to the incident position showed a difference of about 10%, and the response signal was linearly increased. And it has been confirmed that high-resolution and two-dimensional measurements are possible. Conclusion: The developed X-ray spatial dose measuring device was evaluated as suitable for dose measurement of high energy X-ray through confirmation of linearity of response signal, spatial uniformity, high resolution measuring ability and ability to measure spatial dose. We will perform precise measurement of the X-ray beamline in the container scanning system using the X-ray spatial dose distribution measuring device developed through this research.

• Proceedings of the IEEK Conference
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• 2000.06d
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• pp.54-57
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• 2000

In this paper, we propose a new interpolation method by using the motion between two moving image frames. In the proposed method, the movement is detected by using neighborhood pixels of target pixel in the past frame and the present frame. Then, H-shaped pseudomedian filter (below HPMED) is used for the still part of the image and Delta-shaped interpolation filter (below $\Delta$-shaped) for used in the moving part of the image. We detect the movement by comparing the differences between pixels in 4${\times}$5 window of the past frame and the present frame; the difference has a critical value. We simultaneously accomplish checking PSNR(peak signal noise ratio) and subjective assessment that is placed the focus on edge characteristic for assessment of result in computer simulation. The results show that the proposed adaptive method is better than the conventional methods.

• Journal of the Korean Graphic Arts Communication Society
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• v.18 no.2
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• pp.55-68
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• 2000

Joint photographic experts group (JPEG) is a standard still-image compression technique, established by the international organization for standardization (ISO) and international telecommunication standardization sector (ITUT). The standard is intended to be utilized in the various kinds of color still imaging systems as a standard color image coding format. Because JPEG is a lossy compression, the decompressed image pixel values are not the same as the value before compression. Various distortions of JPEG compression and JPEG recompression has been reported in various papers. The Image compressed by JPEG is often recompressed by same type compression method in JPEG. In general, JPEG is a lossy compression and the quality of compressed image is predicted that is varied in according to recompression Q-factor. In this paper, four difference color samples(photo image, gradient image, gradient image, vector drawing image, text image) were compressed in according to various Q-factor, and then the compressed images were recompressed according to various Q-factor once again. As the result, this paper evaluate the variation of image quality and file size in JPEG recompression and recommed the optimum recompression factor.

• Journal of the Semiconductor & Display Technology
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• v.18 no.2
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• pp.63-66
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• 2019

Due to the development of medical imaging technology, different imaging technologies provide a large amount of effective information. However, different imaging method caused the limitations of information integrity by using single type of image. Combining different image together so that doctor can obtain the information from medical image comprehensively. Image registration algorithm based on mutual information has become one of the hotspots in the field of image registration with its high registration accuracy and wide applicability. Because the information theory-based registration technology is not dependent on the gray value difference of the image, and it is very suitable for multimodal medical image registration. However, the method based on mutual information has a robustness problem. The essential reason is that the mutual information itself is not have enough information between the pixel pairs, so that the mutual information is unstable during the registration process. A large number of local extreme values are generated, which finally cause mismatch. In order to overcome the shortages of mutual information registration method, this paper proposes a registration method combined with image spatial structure information and mutual information.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.29 no.1
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• pp.241-254
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• 1999

The purpose of this study was to investigate whether a radiometric analysis of radicular cysts and periapical granulomas is useful in the differential diagnosis. In this experiment, twenty-nine periapical radiographs of the radicular cyst and those periapical granuloma were used. The periapical radiography was taken by intraoral paralleling device. The X-ray film was digitized and digitally filtered to reduce film-grain noise. We estimated density difference of the inner/outer area, roundness or circularity, bone profile or scan line of the margin and cumulative percentage frequency curve of radicular cyst & periapical granuloma. The obtained results were as follows; 1. The differences in density between ROIs of inner and outer area of radicular cysts were smaller than those of periapical granulomas. 2. The equivalent circular diameter was over 6.3mm, there was significant difference between periapical cyst and periapical granuloma. 3. In differential diagnosis of radicular cyst and periapical granuloma using bone profile. sensitivity. specificity and accuracy were considerably high(0.83. 0.86. 0.86) respectively. 4. Cumulative percentage frequency curve of the radicular cyst was closer to the pseudo-pixel value of 50 than average curve, whereas periapical granuloma was closer to that of 0. Hence we conclude that digital radiometric features might be useful in the differential diagnosis between radicular cyst and periapical granuloma.

• Journal of Korea Multimedia Society
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• v.8 no.3
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• pp.313-321
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• 2005

Digital halftoning is a process to produce a binary image so that the original image and its binary counterpart appear similar when observed from a distance. Among digital halftoning methods, error diffusion is a procedure for generating high quality bilevel images from continuous-tone images but blurs the edge information in the bilevel images. To solve this problem, we propose the improved error diffusion using local spatial information of the original images. Based on the fact that the human vision perceives not a pixel but local mean of input image, we compute edge enhancement information(EEI) by appling the ratio of a pixel and its adjacent pixels to local mean. The weights applied to local means is computed using the ratio of local activity measure(LAM) to the difference between input pixels of 3$\times$3 blocks and theirs mean. LAM is the measure of luminance changes in local regions and is obtained by adding the square of the difference between input pixels of 3$\times$3 blocks and theirs mean. We add the value to a input pixel of quantizer to enhance edge. The performance of the proposed method is compared with conventional methods by measuring the edge correlation. The halftone images by using the proposed method show better quality due to the enhanced edge. And the detailed edge is preserved in the halftone images by using the proposed method. Also the proposed method improves the quality of halftone images because unpleasant patterns for human visual system are reduced.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.69-76
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• 2010

The segmentation of moving object in video sequence is a core technique of intelligent image processing system such as video surveillance, traffic monitoring and human tracking. A typical method to segment a moving region from the background is the background subtraction. The steps of background subtraction involve calculating a reference image, subtracting new frame from reference image and then thresholding the subtracted result. One of famous background modeling is Gaussian mixture model (GMM). Even though the method is known efficient and exact, GMM suffers from a problem that includes false pixels in ROI (region of interest), specifically shadow pixels. These false pixels cause fail of the post-processing tasks such as tracking and object recognition. This paper presents a method for removing false pixels included in ROT. First, we subdivide a ROI by using shape characteristics of detected objects. Then, a method is proposed to classify pixels from using histogram characteristic and comparing difference of energy that converts the color value of pixel into grayscale value, in order to estimate whether the pixels belong to moving object area or shadow area. The method is applied to real video sequence and the performance is verified.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.24 no.2
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• pp.279-290
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• 1994

The purpose of this study was to compare the diagnostic accuracy of periapical radiographs and their digitized images for the detection of simulated interproximal carious lesions. A total of 240 interproximal surfaces was used in this study. The case sample was composed of 80 anterior teeth, 80 bicuspids and 80 molars which were prepared in order to distribute the surfaces from carious free to those containing simulated carious lesions of varying depths (0.5㎜, 0.8㎜, and 1.2㎜). The periapical radiographs were taken by paralleling technique and film used was Kodak Ektaspeed(E group). All radiographs were evaluated by five dentist to recognize the true status of simulated carious lesion. They were asked to give a score of 0, 1, 2, or 3. Digitized images were obtained using a commercial video processor(FOTOVIX Ⅱ- XS). And the computer system was 486 DX PC with PC Vision and frame grabber. The 17' display monitor had a resolution of 1280×1024 pixels(0.26㎜ dot pitch). But the one frame of the intraoral radiograph has a resolution of 700×480 pixels and each pixel has a grey level value of 256. All the radiographs and digital images were viewed under uniform subdued lighting in the same reading room. After a week the second interpretation was performed in the same condition. The detection of lesions on the monitor was compared with the finding of simulated interproximal carious lesions on the film images. The results were as follows: 1. When the scoring criteria was dichotomous ; lesion present and not present 1) The overall sensitivity, specificity and diagnostic accuracy of periapical radiographs and their digital images showed no statistically significant difference. 2) The sensitivity and specificity according to the region of teeth and the grade of lesions showed no statistically significant difference between periapical radiographs and their digital images. 2. When estimate the grade of lesions ; score 0, 1, 2, 3 1) The overall diagnostic accuracy was 53.3% on the intraoral films and 52.9% on digital images. There was no significant difference. 2) The diagnostic accuracy according to the region of teeth showed no statistically significant difference between periapical radiographs and their digital images. 3. The degree of agreement and reliability 1) Using gamma value to show the degree of agreement, there was similarity between periapical films and digital images. 2) The reliability of each twice interpretation of periapical films and digital images showed no statistically significant difference. In all cases P value was greater than 0.05, showing that both techniques can be used to detect the incipient and moderate interproximal carious lesions with similar accuracy.