• Journal of Advanced Marine Engineering and Technology
• /
• v.39 no.6
• /
• pp.649-655
• /
• 2015

In this paper, we propose a defogging algorithm for a single image. Dark channel prior (DCP), which is a well-known defogging algorithm, can cause halo artifacts on boundary regions, low-contrast defogging images, and requires a large computational time. To solve these problems, we use histogram information with DCP on transmission estimation regions and a multi-resolution method. Local histogram information can reduce the low-contrast problem on a defogging image, and the multi-resolution method with edge information can reduce the total computational time and halo artifacts. We validate the proposed method by performing experiments on fog images, and we confirm that the proposed algorithm is more efficient and superior than conventional algorithms.

• Journal of Digital Contents Society
• /
• v.16 no.4
• /
• pp.583-593
• /
• 2015

Today, caused by the growth of computer and communication technology, multimedia, especially image data are being used in different application divisions. JPEG2000 that is widely used these days provides a Region-of-Interest(ROI) technique. The extraction of ROI has to be rapidly executed and automatically extracted in a huge amount of image because of being seen preferentially to the users. For this purpose, this paper proposes a method about preferential processing and automatic extraction of ROI using the distribution of edge in the code block of JPEG2000. The steps are the extracting edges, automatical extracting of a practical ROI, grouping the ROI using the ROI blocks, generating the mask blocks and then quantization, ROI coding which is the preferential processing, and EBCOT. In this paper, to show usefulness of the method, we experiment its performance using other methods, and executes the quality evaluation with PSNR between the images not coding an ROI and coding it.

• Journal of Broadcast Engineering
• /
• v.16 no.4
• /
• pp.573-583
• /
• 2011

In this paper, we propose an occlusion compensation algorithm which is used for virtual view generation. In general, since occlusion region is recovered from neighboring pixels by taking the mean value or median value of neighbor pixels, the visual characteristics of a given image are not considered and consequently the accuracy of the compensated occlusion regions is not guaranteed. To solve these problem, we propose an algorithm that considers primary visual characteristics of a given image to compensate the occluded regions by using seam carving algorithm. In the proposed algorithm, we first use Sobel mask to obtain the edge map of a given image and then make it binary digit 0 or 1 and finally thinning process follows. Then, the energy patterns of original and thinned edge map obtained by the modified seam carving method are used to compensate the occlusion regions. Through experiments with many test images, we verify that the proposed algorithm performed better than conventional algorithms.

• Journal of the Korea Convergence Society
• /
• v.8 no.8
• /
• pp.33-40
• /
• 2017

In this paper, we propose a text extraction method by pattern analysis on contour for effective text detection in image. Text extraction algorithms using edge based methods show good performance in images with simple backgrounds, The images of complex background has a poor performance shortcomings. The proposed method simplifies the color of the image by using K-means clustering in the preprocessing process to detect the character region in the image. Enhance the boundaries of the object through the High pass filter to improve the inaccuracy of the boundary of the object in the color simplification process. Then, by using the difference between the expansion and erosion of the morphology technique, the edges of the object is detected, and the character candidate region is discriminated by analyzing the pattern of the contour portion of the acquired region to remove the unnecessary region (picture, background). As a final result, we have shown that the characters included in the candidate character region are extracted by removing unnecessary regions.

• Journal of Korea Multimedia Society
• /
• v.12 no.9
• /
• pp.1217-1232
• /
• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.141-150
• /
• 2011

Precise image-to-image registration is required to process multi-sensor data together. The purpose of this paper is to develop an algorithm that register between high-resolution optical and SAR images using linear features. As a pre-processing step, initial alignment was fulfilled using manually selected tie points to remove any dislocations caused by scale difference, rotation, and translation of images. Canny edge operator was applied to both images to extract linear features. These features were used to design a cost function that finds matching points based on their similarity. Outliers having larger geometric differences than general matching points were eliminated. The remaining points were used to construct a new transformation model, which was combined the piecewise linear function with the global affine transformation, and applied to increase the accuracy of geometric correction.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.3
• /
• pp.2185-2191
• /
• 2015

With the advance of the environment where we can get various multimedia contents, adult image detection has become an important issue these days. In this paper, we suggest a method of robustly detecting navel areas from input images which can be usefully utilized in adult image detection. The suggested algorithm first extracts face regions and extracts candidate nipple areas using a nipple map. Our method then selects only actual nipple regions by filtering candidate areas with geometrical features and an average nipple filter. Subsequently, the method robustly detects navel areas by using the structural relation with the nipple areas and applying edge and saturation images. Experimental results show that the suggested algorithm can effectively detect navel regions.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.4
• /
• pp.444-450
• /
• 1999

This paper deals with several methods: the clustering method that uses k-means algorithm to abstract the area of characters on the image document and the distance function that suits for the HIS coordinate system to cluster the image. For the prepossessing step to recognize this, or the method of characters segmentate, the algorithm to abstract a discrete character is also proposed, using the linking picture element. This algorithm provides the feature that separates any character such as the touching or overlapped character. The methods of projecting and tracking the edge have so far been used to segment them. However, with the new method proposed here, the picture element extracts a discrete character with only one-time projection after abstracting the character string. it is possible to pull out it. dividing the area into the character and the rest (non-character). This has great significance in terms of processing color documents, not the simple binary image, and already received verification that it is more advanced than the previous document processing system.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.8
• /
• pp.48-54
• /
• 1999

A new method for wavelet embedded image coding is presented extending the bases of the Shapiro's algorithm by incorporating edge detection, zerotree scheme, and classified VQ(CVQ). Generally edges in the image are regarded an visually important components and the previous literatures have proved that significant coefficients in wavelet transform domain correspond to the edges in spatial domain. Hence, by identifying the edge elements, the significant coefficient can be easily detected in wavelet domain without investigating descendant coefficients across layer. Hierarchical trees for the significant components are organized, and then CVQ method is applied to these trees. Since the significant information has higher priority in transmission, the simulation shows that our coder provides a superior performance over the conventional method and can be successfully applied to the application areas that require of progressive transmission.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.3C
• /
• pp.279-287
• /
• 2009

In this paper, a hierarchical stereo matching with color information is proposed. To generate an initial disparity map, feature based stereo matching is carried out and to generate a final disparity map, hierarchical stereo matching is carried out. The boundary (edge) region is obtained by segmenting a given image into R, G, B and White components. From the obtained boundary, disparity is extracted. The initial disparity map is generated when the extracted disparity is spread to the surrounding regions by evaluating autocorrelation from each color region. The initial disparity map is used as an initial value for generating the final disparity map. The final disparity map is generated from each color region by changing the size of a block and the search range. 4 test images that are provided by Middlebury stereo vision are used to evaluate the performance of the proposed algorithm objectively. The experiment results show better performance compared to the Graph-cuts and Dynamic Programming methods. In the final disparity map, about 11% of the disparities for the entire image were inaccurate. It was verified that the boundary for the non-contiguous point was clear in the disparity map.