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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 13B, Issue 7 - Dec 2006
Volume 13B, Issue 6 - Dec 2006
Volume 13B, Issue 5 - Oct 2006
Volume 13B, Issue 4 - Aug 2006
Volume 13B, Issue 3 - Jun 2006
Volume 13B, Issue 2 - Apr 2006
Volume 13B, Issue 1 - Feb 2006
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A license plate area segmentation algorithm using statistical processing on color and edge information
Seok Jung-Chul ; Kim Ku-Jin ; Baek Nak-Hoon ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 353~360
DOI : 10.3745/KIPSTB.2006.13B.4.353
This paper presents a robust algorithm for segmenting a vehicle license plate area from a road image. We consider the features of license plates in three aspects : 1) edges due to the characters in the plate, 2) colors in the plate, and 3) geometric properties of the plate. In the preprocessing step, we compute the thresholds based on each feature to decide whether a pixel is inside a plate or not. A statistical approach is applied to the sample images to compute the thresholds. For a given road image, our algorithm binarizes it by using the thresholds. Then, we select three candidate regions to be a plate by searching the binary image with a moving window. The plate area is selected among the candidates with simple heuristics. This algorithm robustly detects the plate against the transformation or the difference of color intensity of the plate in the input image. Moreover, the preprocessing step requires only a small number of sample images for the statistical processing. The experimental results show that the algorithm has 97.8% of successful segmentation of the plate from 228 input images. Our prototype implementation shows average processing time of 0.676 seconds per image for a set of
images, executed on a 3GHz Pentium4 PC with 512M byte memory.
A Snake-Based Segmentation Algorithm for Object with Boundary Concavities
Kim Shin-Hyoung ; Jang Jong-Whan ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 361~368
DOI : 10.3745/KIPSTB.2006.13B.4.361
In this paper we present a snake-based scheme for efficiently detecting contours of objects with boundary concavities. The proposed method is composed of two steps. First, the object`s boundary is detected using the proposed snake model. Second, snake points are optimized by inserting new points and deleting unnecessary points to better describe the object`s boundary. The proposed algorithm can successfully extract objects with boundary concavities. Experimental results have shown that our algorithm produces more accurate segmentation results than the conventional algorithm.
Evaluation of Restoration Schemes for Bi-Level Digital Image Degraded by Impulse Noise
Shin Hyun-Kyung ; Shin Joong-Sang ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 369~376
DOI : 10.3745/KIPSTB.2006.13B.4.369
The degradation and its inverse modeling can achieve restoration of corrupted image, caused by scaled digitization and electronic transmission. De-speckle process on the noisy document(or SAR) images is one of the basic examples. Non-linearity of the speckle noise model may hinder the inverse process. In this paper, our study is focused on investigation of the restoration methods for bi-level document image degraded by the impulse noise model. Our study shows that, on bi-level document images, the weighted-median filter and the Lee filter methods are very effective among other spatial filtering methods, but wavelet filter method is ineffective in aspect of processing speed: approximately 100 times slower. Optimal values of the weight to be used in the weighted median filter are investigated and presented in this paper.
Template Check and Block Matching Method for Automatic Defects Detection of the Back Light Unit
Han Chang-Ho ; Cho Sang-Hee ; Oh Choon-Suk ; Ryu Young-Kee ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 377~382
DOI : 10.3745/KIPSTB.2006.13B.4.377
In this paper, two methods based on the use of morphology and pattern matching prior to detect classified defects automatically on the back light unit which is a part of display equipments are proposed. One is the template check method which detects small size defects by using closing and opening method, and the other is the block matching method which detects big size defects by comparing with four regions of uniform blocks. The TC algorithm also can detect defects on the non-uniform pattern of BLU by using revised Otsu method. The proposed method has been implemented on the automatic defect detection system we developed and has been tested image data of BLU captured by the system.
Multi-class Feedback Algorithm for Region-based Image Retrieval
Ko Byoung-Chul ; Nam Jae-Yeal ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 383~392
DOI : 10.3745/KIPSTB.2006.13B.4.383
In this paper, we propose a new relevance feedback algorithm using Probabilistic Neural Networks(PNN) while supporting multi-class learning. Then, to validate the effectiveness of our feedback approach, we incorporate the proposed algorithm into our region-based image retrieval tool, FRIP(Finding Regions In the Pictures). In our feedback approach, there is no need to assume that feature vectors are independent, and as well as it allows the system to insert additional classes for detail classification. In addition, it does not have a long computation time for training because it only has four layers. In the PNN classification process, we store the user`s entire past feedback actions as a history in order to improve performance for future iterations. By using a history, our approach can capture the user`s subjective intension more precisely and prevent retrieval performance errors which originate from fluctuating or degrading in the next iteration. The efficacy of our method is validated using a set of 3000 images derived from a Corel-photo CD.
A Study on Face Recognition based on Partial Least Squares
Lee Chang-Beom ; Kim Do-Hyang ; Baek Jang-Sun ; Park Hyuk-Ro ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 393~400
DOI : 10.3745/KIPSTB.2006.13B.4.393
There are many feature extraction methods for face recognition. We need a new method to overcome the small sample problem that the number of feature variables is larger than the sample size for face image data. The paper considers partial least squares(PLS) as a new dimension reduction technique for feature vector. Principal Component Analysis(PCA), a conventional dimension reduction method, selects the components with maximum variability, irrespective of the class information. So, PCA does not necessarily extract features that are important for the discrimination of classes. PLS, on the other hand, constructs the components so that the correlation between the class variable and themselves is maximized. Therefore PLS components are more predictive than PCA components in classification. The experimental results on Manchester and ORL databases shows that PLS is to be preferred over PCA when classification is the goal and dimension reduction is needed.
Feature Extraction by Line-clustering Segmentation Method
Hwang Jae-Ho ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 401~408
DOI : 10.3745/KIPSTB.2006.13B.4.401
In this paper, we propose a new class of segmentation technique for feature extraction based on the statistical and regional classification at each vertical or horizontal line of digital image data. Data is processed and clustered at each line, different from the point or space process. They are designed to segment gray-scale sectional images using a horizontal and vertical line process due to their statistical and property differences, and to extract the feature. The techniques presented here show efficient results in case of the gray level overlap and not having threshold image. Such images are also not easy to be segmented by the global or local threshold methods. Line pixels inform us the sectionable data, and can be set according to cluster quality due to the differences of histogram and statistical data. The total segmentation on line clusters can be obtained by adaptive extension onto the horizontal axis. Each processed region has its own pixel value, resulting in feature extraction. The advantage and effectiveness of the line-cluster approach are both shown theoretically and demonstrated through the region-segmental carotid artery medical image processing.
Extraction of Text Regions from Spam-Mail Images Using Color Layers
Kim Ji-Soo ; Kim Soo-Hyung ; Han Seung-Wan ; Nam Taek-Yong ; Son Hwa-Jeong ; Oh Sung-Ryul ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 409~416
DOI : 10.3745/KIPSTB.2006.13B.4.409
In this paper, we propose an algorithm for extracting text regions from spam-mail images using color layer. The CLTE(color layer-based text extraction) divides the input image into eight planes as color layers. It extracts connected components on the eight images, and then classifies them into text regions and non-text regions based on the component sizes. We also propose an algorithm for recovering damaged text strokes from the extracted text image. In the binary image, there are two types of damaged strokes: (1) middle strokes such as `ㅣ` or `ㅡ` are deleted, and (2) the first and/or last strokes such as `ㅇ` or `ㅁ` are filled with black pixels. An experiment with 200 spam-mail images shows that the proposed approach is more accurate than conventional methods by over 10%.
Detecting Faces on Still Images using Sub-block Processing
Yoo Chae-Gon ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 417~420
DOI : 10.3745/KIPSTB.2006.13B.4.417
Detection of faces on still color images with arbitrary backgrounds is attempted in this paper. The newly proposed method is invariant to arbitrary background, number of faces, scale, orientation, skin color, and illumination through the steps of color clustering, cluster scanning, sub-block processing, face area detection, and face verification. The sub-block method makes the proposed method invariant to the size and the number of faces in the image. The proposed method does not need any pre-training steps or a preliminary face database. The proposed method may be applied to areas such as security control, video and photo indexing, and other automatic computer vision-related fields.
Development of a Adaptive Knowledge Base Object Model for Intelligent Tutoring System
Kim Yong-Beom ; Kim Yung-Sik ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 421~428
DOI : 10.3745/KIPSTB.2006.13B.4.421
Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners` variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the `Knowledge Base Object Medel`, which is based on connectionist` in cognition structure, represents learner`s knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.
MLP Design Method Optimized for Hidden Neurons on FPGA
Kyoung Dong-Wuk ; Jung Kee-Chul ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 429~438
DOI : 10.3745/KIPSTB.2006.13B.4.429
Neural Networks(NNs) are applied for solving a wide variety of nonlinear problems in several areas, such as image processing, pattern recognition etc. Although NN can be simulated by using software, many potential NN applications required real-time processing. Thus they need to be implemented as hardware. The hardware implementation of multi-layer perceptrons(MLPs) in several kind of NNs usually uses a fixed-point arithmetic due to a simple logic operation and a shorter processing time compared to the floating-point arithmetic. However, the fixed-point arithmetic-based MLP has a drawback which is not able to apply the MLP software that use floating-point arithmetic. We propose a design method for MLPs which has the floating-point arithmetic-based fully-pipelining architecture. It has a processing speed that is proportional to the number of the hidden nodes. The number of input and output nodes of MLPs are generally constrained by given problems, but the number of hidden nodes can be optimized by user experiences. Thus our design method is using optimized number of hidden nodes in order to improve the processing speed, especially in field of a repeated processing such as image processing, pattern recognition, etc.
A New Self-Organizing Map based on Kernel Concepts
Cheong Sung-Moon ; Kim Ki-Bom ; Hong Soon-Jwa ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 439~448
DOI : 10.3745/KIPSTB.2006.13B.4.439
Previous recognition/clustering algorithms such as Kohonen SOM(Self-Organizing Map), MLP(Multi-Layer Percecptron) and SVM(Support Vector Machine) might not adapt to unexpected input pattern. And it`s recognition rate depends highly on the complexity of own training patterns. We could make up for and improve the weak points with lowering complexity of original problem without losing original characteristics. There are so many ways to lower complexity of the problem, and we chose a kernel concepts as an approach to do it. In this paper, using a kernel concepts, original data are mapped to hyper-dimension space which is near infinite dimension. Therefore, transferred data into the hyper-dimension are distributed spasely rather than originally distributed so as to guarantee the rate to be risen. Estimating ratio of recognition is based on a new similarity-probing and learning method that are proposed in this paper. Using CEDAR DB which data is written in cursive letters, 0 to 9, we compare a recognition/clustering performance of kSOM that is proposed in this paper with previous SOM.
Intelligent Characters for Fighting Action Games applied Energy Points
Lee Myun-Sub ; Cho Byeong-Heon ; Jung Sung-Hoon ; Seong Yeong-Rak ; Oh Ha-Ryoung ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 449~456
DOI : 10.3745/KIPSTB.2006.13B.4.449
This paper proposes intelligent characters for fighting action games to which energy points are applied for more realistic implementation than those of previous researches. The intelligent characters decide their actions in consideration of their energy level as well as a current action, the step of the action, the distance, and past actions of opponent characters that were used in existing intelligent ones. We used two types of energy, HP(Health Point) and MP(Mana Point) that were frequently employed in recent on-line games. We experimented with proposed intelligent characters to investigate whether the intelligent characters learn proper actions and cope with opponent characters in consideration of their energy levels. Experimental results showed that the intelligent characters reacted with the best actions to obtain high score if their energy is sufficient, Otherwise, they did the actions to(that?) recharge their energy. From this observation, we could conclude that the proposed intelligent characters worked well and did effective actions in consideration of the their energy.
Improving the Classification Accuracy Using Unlabeled Data: A Naive Bayesian Case
Lee Chang-Hwan ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 457~462
DOI : 10.3745/KIPSTB.2006.13B.4.457
In many applications, an enormous amount of unlabeled data is available with little cost. Therefore, it is natural to ask whether we can take advantage of these unlabeled data in classification learning. In this paper, we analyzed the role of unlabeled data in the context of naive Bayesian learning. Experimental results show that including unlabeled data as part of training data can significantly improve the performance of classification accuracy. The effect of using unlabeled data is especially important in case labeled data are sparse.
A Study on Object Tracking using Variable Search Block Algorithm
Min Byoung-Muk ; Oh Hae-Seok ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 463~470
DOI : 10.3745/KIPSTB.2006.13B.4.463
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.
Color Contrast Evaluation Algorithm Considering Color Temperature Feeling
Jang Young-Gun ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 471~478
DOI : 10.3745/KIPSTB.2006.13B.4.471
In this paper, two color contrast evaluation algorithms, W3C and NSSC algorithms are compared and investigated to select proper criteria of the color contrast of text-background color combinations in web documents. The relationship between the color contrast defined by existing formula and the readability rating is not perfect and there is quite a bit of variance, in particular, there is some substantial outlier. I modify the NSSC algorithm to apply all colors and compare the two algorithms to apply same color combinations of web safe colors. A new algorithm considering color temperature feeling as a component of the color contrast is proposed and implemented. As the results of this study, the existing two algorithms are not contradictory to each other, 82% of all color combinations of web safe colors are not proper combinations according to W3C guide which provide severe restriction to select colors in web documents compared to NSSC algorithm. Experimental test shows proposed algorithm is superior to the W3C algorithm with respect to the linearity of relationship between color contrast and readability rating. It means a color temperature feeling is an effective component of a color contrast. But to determine best contribution ratio of the color temperature feeling, further study is required and it is related to Hangul font style and size. The more popular a mobile color display is used, the more important accessibility factor a color contrast will be.
Implementation of Iconic Language for the Language Support System of the Language Disorders
Choo Kyo-Nam ; Woo Yo-Seob ; Min Hong-Ki ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 479~488
DOI : 10.3745/KIPSTB.2006.13B.4.479
The iconic language interlace is designed to provide more convenient environments for communication to the target system than the keyboard-based interface. For this work, tendencies and features of vocabulary are analyzed in conversation corpora constructed from the corresponding domains with high degree of utilization, and the meaning and vocabulary system of iconic language are constructed through application of natural language processing methodologies such as morphological, syntactic and semantic analyses. The part of speech and grammatical rules of iconic language are defined in order to make the situation corresponding the icon to the vocabulary and meaning of the Korean language and to communicate through icon sequence. For linguistic ambiguity resolution which may occur in the iconic language and for effective semantic processing, semantic data focused on situation of the iconic language are constructed from the general purpose Korean semantic dictionary and subcategorization dictionary. Based on them, the Korean language generation from the iconic interface in semantic domain is suggested.
Feature Filtering Methods for Web Documents Clustering
Park Heum ; Kwon Hyuk-Chul ;
The KIPS Transactions:PartB, volume 13B, issue 4, 2006, Pages 489~498
DOI : 10.3745/KIPSTB.2006.13B.4.489
Clustering results differ according to the datasets and the performance worsens even while using web documents which are manually processed by an indexer, because although representative clusters for a feature can be obtained by statistical feature selection methods, irrelevant features(i.e., non-obvious features and those appearing in general documents) are not eliminated. Those irrelevant features should be eliminated for improving clustering performance. Therefore, this paper proposes three feature-filtering algorithms which consider feature values per document set, together with distribution, frequency, and weights of features per document set: (l) features filtering algorithm in a document (FFID), (2) features filtering algorithm in a document matrix (FFIM), and (3) a hybrid method combining both FFID and FFIM (HFF). We have tested the clustering performance by feature selection using term frequency and expand co link information, and by feature filtering using the above methods FFID, FFIM, HFF methods. According to the results of our experiments, HFF had the best performance, whereas FFIM performed better than FFID.