• 전자공학회논문지 IE
• /
• v.46 no.4
• /
• pp.57-65
• /
• 2009

This paper presents the image contrast enhancement technique suitable for local dimming backlight of small-sized mobile display while achieving the reduction of the power consumption. In addition to the large-sized TFT-LCD, small-sized one has adopted LED for backlight. Since, conventionally, LED was mounted on the side edge of a display panel, global dimming method has been widely used. However, recently, new advanced method of local dimming by placing the LED to the backside of the display panel and it raised the necessity of sub-blocked processing after partitioning the target image. When the sub-blocked image has low brightness, the supply current of a backlight LED is reduced, which gives both enhancement of contrast ratio and power consumption reduction. In this paper, we propose simple and improved image enhancement algorithm suitable for the small-sized mobile display. After partitioning the input image by equal sized blocks and analyzing the pixel information in each block, we realize the primary contrast enhancement by independently processing the sub-blocks using the information such as histogram, mean, and standard deviation values of luminance(Y) component. And then resulting information is transferred to each backlight control unit for local dimming to realize the secondary contrast enhancement as well as reduction of power consumption.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.44 no.4
• /
• pp.55-62
• /
• 2007

This paper proposes a defective pixel detection algorithm and its hardware structure for CCD/CMOS image sensor. In previous algorithms, the characteristics of image have not been considered. Also, some algorithms need quite a time to detect defective pixels. In order to make up for those disadvantages, the proposed defective pixel detection method detects defective pixels efficiently by considering the edges in the image and verifies them using several frames while checking scene-changes. Whenever scene-change is occurred, potentially defective pixels are checked and confirmed whether it is defective or not. Test results showed that the correct detection rate in a frame was increased 6% and the defective pixel verification time was decreased 60%. The proposed algorithm was implemented with verilog HDL. The edge indicator in color interpolation block was reused. Total logic gate count was 5.4k using 0.25um CMOS standard cell library.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.3
• /
• pp.227-239
• /
• 2008

Processing LiDAR (Light Detection And Ranging) data obtained from ALS (Airborne Laser Scanning) systems mainly involves organization and segmentation of the data for 3D object modeling and mapping purposes. The ALS systems are viable and becoming more mature technology in various applications. ALS technology requires complex integration of optics, opto-mechanics and electronics in the multi-sensor components, Le. data captured from GPS, INS and laser scanner. In this study, digital image processing techniques mainly were implemented to gray level coded image of the LiDAR data for building extraction and superstructures segmentation. One of the advantages to use gray level image is easy to apply various existing digital image processing algorithms. Gridding and quantization of the raw LiDAR data into limited gray level might introduce smoothing effect and loss of the detail information. However, smoothed surface data that are more suitable for surface patch segmentation and modeling could be obtained by the quantization of the height values. The building boundaries were precisely extracted by the robust edge detection operator and regularized with shape constraints. As for segmentation of the roof structures, basically region growing based and gap filling segmentation methods were implemented. The results present that various image processing methods are applicable to extract buildings and to segment surface patches of the superstructures on the roofs. Finally, conceptual methodology for extracting characteristic information to reconstruct roof shapes was proposed. Statistical and geometric properties were utilized to segment and model superstructures. The simulation results show that segmentation of the roof surface patches and modeling were possible with the proposed method.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.10
• /
• pp.2615-2628
• /
• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.

• Tunnel and Underground Space
• /
• v.29 no.3
• /
• pp.184-196
• /
• 2019

This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.2
• /
• pp.139-146
• /
• 2016

Recently, popularity of 3D technology has been growing significantly and it has many application parts in the various fields of industry. In order to overcome the limitations of 2D machine vision technologies based on 2D image, we need the 3D measurement technologies. There are many 3D measurement methods as such scanning probe microscope, phase shifting interferometry, confocal scanning microscope, white-light scanning interferometry, and so on. In this paper, we have used the extended depth of focus (EDF) algorithm among 3D measurement methods. The EDF algorithm is the method which extracts the 3D information from 2D images acquired by short range depth camera. In this paper, we propose the EDF algorithm using the edge informations of images and the average values of all pixel on z-axis to improve the performance of conventional method. To verify the performance of the proposed method, we use the various synthetic images made by point spread function(PSF) algorithm. We can correctly make a comparison between the performance of proposed method and conventional one because the depth information of these synthetic images was known. Through the experimental results, the PSNR of the proposed algorithm was improved about 1 ~ 30 dB than conventional method.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.3
• /
• pp.8-15
• /
• 2007

Recently, it is important to process multimedia data efficiently. Especially, in case of retrieval of multimedia information, technique of user interface and retrieval technique are necessary. This paper proposes a new technique which detects cuts effectively in compressed image information by MPEG. A cut is a turning point of scenes. The cut-detection is the basic work and the first-step for video indexing and retrieval. Existing methods have a weak point that they detect wrong cuts according to change of a screen such as fast motion of an object, movement of a camera and a flash. Because they compare between previous frame and present frame. The proposed technique detects shots at first using DC(Direct Current) coefficient of DCT(Discrete Cosine Transform). The database is composed of these detected shots. Features are extracted by HMMD color model and edge histogram descriptor(EHD) among the MPEG-7 visual descriptors. And detections are performed in sequence by the proposed matching technique. Through this experiments, an improved video segmentation system is implemented that it performs more quickly and precisely than existing techniques have.

• Journal of Korea Multimedia Society
• /
• v.21 no.2
• /
• pp.147-157
• /
• 2018

Alzheimer's disease has the significant factors for the both specific and characteristic features according to the disease progressing that are the volumetry and surface area by the brain hippocampus shrinking and thinning. However, we have suggested a shape analysis to calculate the variance by the roughness, coarseness or uneven surface on 3D MR images. For the reasons we have presented two methods: the first method is the distance calculation from major axis to edge points and the second method is the distance calculation from centroidal point to edge points on a coronal plane. Then we selected the shortest distance and the longest distance in each slice and analyzed the ANOVA and average distances. Consequently we obtained the available and great results by the longest distance of the axial and centroidal point. The results of average distances were 44.85(AD), 45.04(MCI) and 49.31(NC) from the axial points and 39.30(AD), 39.58(MCI) and 44.78(NC) from centroidal points respectively. Finally the distance variations for the easily recognized visualization were shown by the color mapping. This research could be provided an indicator of biomarkers that make diagnosis and prognosis the Alzheimer's diseases in the future.

• The KIPS Transactions:PartB
• /
• v.17B no.1
• /
• pp.37-46
• /
• 2010

In this paper we have presented a two dimensional model based tracking system using improved chamfer matching. Conventional chamfer matching could not calculate similarity well between the object and image when there is very cluttered background. Then we have improved chamfer matching to calculate similarity well even in very cluttered background with edge and corner feature points. Improved chamfer matching is used as likelihood function of particle filter which tracks the geometric object. Geometric model which uses edge and corner feature points, is a discriminant descriptor in color changes. Particle Filter is more non-linear tracking system than Kalman Filter. Then the presented method uses geometric model, particle filter and improved chamfer matching for tracking object in complex environment. In experimental result, the robustness of our system is proved by comparing other methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.35 no.6
• /
• pp.599-608
• /
• 2017

Cracks on the asphalt road surface can affect the speed of the car, the consumption of fuel, the ride quality of the road, and the durability of the road surface. Such cracks in roads can lead to very dangerous consequences for long periods of time. To prevent such risks, it is necessary to identify cracks and take appropriate action. It takes too much time and money to do it. Also, it is difficult to use expensive laser equipment vehicles for initial cost and equipment operation. In this paper, we propose an effective detection method of road surface defect using ROI (Region of Interest) setting and cany edge detection method using UAV image. The results of this study can be presented as efficient method for road surface flaw detection and maintenance using UAV. In addition, it can be used to detect cracks such as various buildings and civil engineering structures such as buildings, outer walls, large-scale storage tanks other than roads, and cost reduction effect can be expected.