• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.1
• /
• pp.78-84
• /
• 2015

Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.

• Journal of Internet Computing and Services
• /
• v.8 no.5
• /
• pp.117-123
• /
• 2007

Catadioptric mirrors are widely used in automatic surveillance system. The major drawback of catadioptric mirror is its unequal image resolution. Equidistance catadioptric mirrir can be the solution to this problem. The exact axial alignment and the exact mount of mirror are the sources that can be avoided but the focal length variation is inevitable. In this paper, the effects of focal length variation on the computation of depth and height of object' point are explained and the effective and simple focal length finding algorithm is presented. First two object's points are selected, and the counterparts on the other stereo image are to be found using MSE criterion. Using four pixel distance from the image center, the assumed focal length is calculated. If the obtained focal length is different from the exact focal length, 24mm, the focal length value is modified by the proposed method. The method is very simple and gives the comparable results with the earlier sophisticated method.

• Korean Journal of Remote Sensing
• /
• v.30 no.6
• /
• pp.817-827
• /
• 2014

In the satellite remote sensing, the operational environment of the satellite sensor causes image degradation during the image acquisition. The degradation results in noise and blurring which badly affect identification and extraction of useful information in image data. This study proposes a maximum a posteriori (MAP) estimation using Point-Jacobian iteration to restore a degraded image. The proposed method assumes a Gaussian additive noise and Markov random field of spatial continuity. The proposed method employs a neighbor window of spoke type which is composed of 8 line windows at the 8 directions, and a boundary adjacency measure of Mahalanobis square distance between center and neighbor pixels. For the evaluation of the proposed method, a pixel-wise classification was used for simulation data using various patterns similar to the structure exhibited in high resolution imagery and an unsupervised segmentation for the remotely-sensed image data of 1 mspatial resolution observed over the north area of Anyang in Korean peninsula. The experimental results imply that it can improve analytical accuracy in the application of remote sensing high resolution imagery.

• The KIPS Transactions:PartB
• /
• v.13B no.4 s.107
• /
• pp.463-470
• /
• 2006

It is difficult to track and extract the movement of an object through a camera exactly because of noises and changes of the light. The fast searching algorithm is necessary to extract the object and to track the movement for realtime image. In this paper, we propose the correct and fast algorithm using the variable searching area and the background image change method to robustic for the change of background image. In case the threshold value is smaller than reference value on an experimental basis, change the background image. When it is bigger, we decide it is the point of the time of the object input and then extract boundary point of it through the pixel check. The extracted boundary points detect precise movement of the object by creating area block of it and searching block that maintaining distance. The designed and embodied system shows more than 95% accuracy in the experimental results.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.117-140
• /
• 2013

Hindi is the most widely spoken language in India, with more than 300 million speakers. As there is no separation between the characters of texts written in Hindi as there is in English, the Optical Character Recognition (OCR) systems developed for the Hindi language carry a very poor recognition rate. In this paper we propose an OCR for printed Hindi text in Devanagari script, using Artificial Neural Network (ANN), which improves its efficiency. One of the major reasons for the poor recognition rate is error in character segmentation. The presence of touching characters in the scanned documents further complicates the segmentation process, creating a major problem when designing an effective character segmentation technique. Preprocessing, character segmentation, feature extraction, and finally, classification and recognition are the major steps which are followed by a general OCR. The preprocessing tasks considered in the paper are conversion of gray scaled images to binary images, image rectification, and segmentation of the document's textual contents into paragraphs, lines, words, and then at the level of basic symbols. The basic symbols, obtained as the fundamental unit from the segmentation process, are recognized by the neural classifier. In this work, three feature extraction techniques-: histogram of projection based on mean distance, histogram of projection based on pixel value, and vertical zero crossing, have been used to improve the rate of recognition. These feature extraction techniques are powerful enough to extract features of even distorted characters/symbols. For development of the neural classifier, a back-propagation neural network with two hidden layers is used. The classifier is trained and tested for printed Hindi texts. A performance of approximately 90% correct recognition rate is achieved.

• Journal of KIISE:Computer Systems and Theory
• /
• v.34 no.5_6
• /
• pp.228-237
• /
• 2007

displacement mapping enables us to add realistic details to polygonal meshes without changing geometry. We present a real-time artifacts-free inverse displacement mapping method. In each pixel, we construct a ray and trace the ray through the displacement map to find an intersection. To skip empty regions safely, we traverse the image pyramid of displacement map in top-down order. Furthermore, when the displacement map is enlarged, intersection with bilinear interpolated displacement map can be found. When the displacement map is at distance, our method supports mipmap-like prefiltering to enhance image quality and speed. Experimental results show that our method can produce correct images even at grazing view angles. Rendering speed of a test scene is over hundreds of frames per second and the influence of resolution of displacement map to rendering speed is little. Our method is simple enough to be added to existing virtual reality systems easily.

• Journal of Korea Society of Industrial Information Systems
• /
• v.22 no.2
• /
• pp.1-13
• /
• 2017

In This Paper, we find the Target Candidate Region and the Location of the Candidate Region by Performing the Morphological Difference Calculation and Pixel Labeling for Robust Small Target Detection in Infrared Image with low SNR. Conventional Target Detection Methods based on Morphology Algorithms are low in Detection Accuracy due to their Vulnerability to Clutter in Infrared Images. To Address the Problem, Target Signal Enhancement and Background Clutter Suppression are Achieved Simultaneously by Combining Moravec Algorithm and LCM (Local Contrast Measure) Algorithm to Classify the Target and Noise in the Candidate Region. In Addition, the Proposed Algorithm can Efficiently Detect Multiple Targets by Solving the Problem of Limited Detection of a Single Target in the Target Detection method using the Morphology Operation and the Gaussian Distance Function Which were Developed for Real time Target Detection.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.11
• /
• pp.2538-2543
• /
• 2012

The Percutaneous Coronary intervention is a typical way of testing which could be performance to treat a stenosed region by inserting a stent using catheter. In this case, choosing the best stent amongst various kinds of stent for performing an intervention is the most difficult process. For the reason, a width of the blood vessel which is stenosed must be correctly measured to help an operator choose right size of stent. So based on pixel, a width of the blood vessel measured by using the way of Euclidean distance after designing a center-line of vessel from a certain point assigned by operator is shown as a profile in this study. This study would be used as a goof reference for operators when choosing right size of stent.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.29B no.7
• /
• pp.52-61
• /
• 1992

An iterative scheme for computing the three-dimensional position and the surface orientation of an opaque object from a singel shaded image is proposed. This method demonstrates that calculating the depth(distance) between the camera and the object from one shaded video image is possible. Most previous research works on $'Shape from Shading$' problem, even in the $'Photometric Stereo Method$', invoved the determination of surface orientation only. To measure the depth of an object, depth of the object, and the reflectance properties of the surface. Assuming that the object surface is uniform Lambertian the measured intensity level at a given image pixel*x,y0becomes a function of surface orientation and depth component of the object. Derived Image Irradiance Equation can`t be solved without further informations since three unknown variables(p,q and D) are in one nonlinear equation. As an additional constraints we assume that surface satisfy smoothness conditions. Then equation can be solved relaxatively using standard methods of TEX>$'Calculus of VariationTEX>$'. After checking the sensitivity of the algorithm to the errors ininput parameters, the theoretical results is tested by experiments. Three objects (plane, cylinder, and sphere)are used. Thees initial results are very encouraging since they match the theoretical calculations within 20$\%$ error in simple experiments.> error in simple experiments.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.553-559
• /
• 2004

In todays security industry, personal identification is also based on biometric. Biometric identification is performed basing on the measurement and comparison of physiological and behavioral characteristics, Biometric for recognition includes voice dynamics, signature dynamics, hand geometry, fingerprint, iris, etc. Iris can serve as a kind of living passport or living password. Iris recognition system is the one of the most reliable biometrics recognition system. This is applied to client/server system such as the electronic commerce and electronic banking from stand-alone system or networks, ATMs, etc. A new algorithm using nonlinear function in recognition process is proposed in this paper. An algorithm is proposed to determine the localized iris from the iris image received from iris input camera in client. For the first step, the algorithm determines the center of pupil. For the second step, the algorithm determines the outer boundary of the iris and the pupillary boundary. The localized iris area is transform into polar coordinates. After performing three times Wavelet transformation, normalization was done using sigmoid function. The converting binary process performs normalized value of pixel from 0 to 255 to be binary value, and then the converting binary process is compare pairs of two adjacent pixels. The binary code of the iris is transmitted to the by server. the network. In the server, the comparing process compares the binary value of presented iris to the reference value in the University database. Process of recognition or rejection is dependent on the value of Hamming Distance. After matching the binary value of presented iris with the database stored in the server, the result is transmitted to the client.