• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.86-97
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• 2011

This paper presents a novel algorithm to detect more accurate road lane with image sensor-based color classification and directional edge clustering. With treatment of road region and lane as a recognizable color object, the classification of color cues is processed by an iterative optimization of statistical parameters to each color object. These clustered color objects are taken into considerations as initial kernel information for color object detection and recognition. In order to improve the limitation of object classification using the color cues, the directional edge cures within the estimated region of interest in the lane boundary (ROI-LB) are clustered and combined. The results of color classification and directional edge clustering are optimally integrated to obtain the best detection of road lane. The characteristic of the proposed system is to obtain robust result to all real road environments because of using non-parametric approach based only on information of color and edge clustering without a particular mathematical road and lane model. The experimental results to the various real road environments and imaging conditions are presented to evaluate the effectiveness of the proposed method.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.359-371
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• 2011

Edge detection in images is an important step in image segmentation and object recognition as preprocessing for image processing. This paper presents a new edge detection using local histogram analysis based on wavelet transform. In this work, the wavelet transform uses three components (horizontal, vertical and diagonal) to find the magnitude of the gradient vector, instead of the conventional approach in which tw components are used. We compare the magnitude of the gradient vector with the threshold that is obtained from a local histogram analysis to conclude that an edge is present or not. Some experimental results for our edge detector with a Sobel, Canny, Scale Multiplication, and Mallat edge detectors on sample images are given and the performances of these edge detectors are compared in terms of quantitative and qualitative measures. Our detector performs better than the other wavelet-based detectors such as Scale Multiplication and Mallat detectors. Our edge detector also preserves a good performance even if the Sobel and Canny detector are sharply low when the images are highly corrupted.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1479-1486
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• 2011

In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.415-433
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• 1998

Digora system is an intraoral indirect digital radiography system utilizing storage phosphor image plate. It has wide dynamic range which allows it to decrease the patient s exposure time and may increase diagnostic ability through image processing (such as edge enhancement, grey scale conversion, brightness change, and contrast enhancement). And also, it can transmit and storage image information. The purpose of this study was to evaluate the diagnostic ability of artificial proximal caries between Conventional radiograph and Digora images(unenhanced image, brightness & contrast controlled image, and edge enhanced image). ROC(Receiver Operating Characteristic) analysis, paired t-tests, and F-tests were done for the statistical evaluation of detectability. The following results were acquired: 1. In Grade I lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.953, 0.933, 0.965, 0.978 (p>0.05). 2. In Grade II lesions, the mean ROC areas of Conventional radiograph, Digora unenhanced image, Digora controlled image, and Digora edge enhanced image were 0.969, 0.964, 0.988, 0.994. Among theses areas, there was just statistical significance between Diagnostic abilities of Digora edge enhanced image and Conventional radiograph (p<0.05). 3. In the Interobserver variability, the ROC curve areas of Digora edge enhanced image was lowermost in these areas, regardless of the Carious lesion depths. In conclusion, intraoral indirect digital system, Digora system, has the potential possibility as an alternative of Conventional radiograph in the diagnosis of proximal caries.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.50-53
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• 2007

This paper presents face features detection and a new physiological neuro-fuzzy learning method by using two-dimensional variances based on variation of gray level and by learning for a statistical distribution of the detected face features. This paper reports a method to learn by not using partial face image but using global face image. Face detection process of this method is performed by describing differences of variance change between edge region and stationary region by gray-scale variation of global face having featured regions including nose, mouse, and couple of eyes. To process the learning stage, we use the input layer obtained by statistical distribution of the featured regions for performing the new physiological neuro-fuzzy algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.717-724
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• 2016

This paper proposes a change detection method based on the covariance matrices of color and edge gradient in a color video. The YCbCr color format was used instead of RGB. The color covariance matrix was calculated from the CbCr-channels and the edge gradient covariance matrix was calculated from the Y-channels. The covariance matrices were effectively calculated at each pixel by calculating the sum, squared sum, and sum of two values' multiplication of a rectangle area using the integral images from a background image. The background image was updated by a running the average between the background image and a current frame. The change areas in a current frame image against the background were detected using the Mahalanobis distance, which is a measure of the statistical distance using covariance matrices. The experimental results of an expressway color video showed that the proposed approach can effectively detect change regions for color and edge gradients against the background.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.9
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• pp.930-935
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• 2014

A Gabor filter is a linear filter used for edge detectionas frequency and orientation representations of Gabor filters are similar to those of the human visual system. In this thesis, we propose a pedestrian detection algorithm using a Gabor filter bank. In order to extract the features of the pedestrian, we use various image processing algorithms and data structure algorithms. First, color image segmentation is performed to consider the information of the RGB color space. Second, histogram equalization is performed to enhance the brightness of the input images. Third, convolution is performed between a Gabor filter bank and the enhanced images. Fourth, statistical values are calculated by using the integral image (summed area table) method. The calculated statistical values are used for the feature matrix of the pedestrian area. To evaluate the proposed algorithm, the INRIA pedestrian database and SVM (Support Vector Machine) are used, and we compare the proposed algorithm and the HOG (Histogram of Oriented Gradient) pedestrian detector, presentlyreferred to as the methodology of pedestrian detection algorithm. The experimental results show that the proposed algorithm is more accurate compared to the HOG pedestrian detector.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.365-372
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• 1996

The researches to acquire diagnostic parameters from ultrasonic images are advanced with the progress of the digital image processing technique. Especially, the detection of endocardial boundary is very important in ultrasonic images, because endocardial boundary is used as a clinical parameter to estimate both the cardiac area and the variation of cardiac volume. Various methods to detect cardiac boundary are proposed, but these are insufficient to detect boundary. In this paper, an algorithm that detects the endocardial boundary, expanding the cavity region from the center using statistical information, is proposed The value of mean and sty:nd, wd deviation in cavity region is lower than those in muscle re- gion. Therefore, if we define the multiplication of mean and standard deviation as homogeneous coefficient, it can lead to conclusion that the pixels with small variation of these coefficleno are cavity region, and extraction of endocardial boundary from cavity region is possible. The proposed method detected endocardial boundary more effectively than edge based or threshold based method and is robuster to noise than radial searching method that has high dependency for center position.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2814-2818
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• 2000

This paper describes an image processing algorithm capable of recognizing the road lane using a CDF (Cumulative Distribution Function). which is designed for the model function of the road lane. The CDF has distinctive peak points at the vicinity of the lane direction because of the directional and positional continuities of the lane. We construct a scatter diagram by collecting the edge pixels with the direction corresponding to the peak point of the CDF and carry out the principal axis-based line fitting for the scatter diagram to obtain the lane information. As noises play the role of making a lot of similar features to the lane appear and disappear in the image we introduce a recursive estimator of the function to reduce the noise effect and a scene understanding index (SUI) formulated by statistical parameters of the CDF to prevent a false alarm or miss detection. The proposed algorithm has been implemented in a real time on the video data obtained from a test vehicle driven in a typical highway.