• The Journal of the Korea Contents Association
• /
• v.6 no.9
• /
• pp.19-27
• /
• 2006

Mean shift procedure is applied for the data points in the joint spatial-range domain and achieves a high quality. However, a color image is segmented differently according to the inputted spatial parameter or range parameter and the demerit is that the image is broken into many small regions in case of the small parameter. In this paper, to improve this demerit, we propose the method that groups similar regions using region merging method for over-segmented images. The proposed method converts a over-segmented image in RGB color space into in HSI color space and merges similar regions by hue information. Here, to preserve edge information, the region merge constraints are used to decide whether regions are merged or not. After then, we merge the regions in RGB color space for non-processed regions in HSI color space. Experimental results show the superiority in region's segmentation results.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.46 no.2
• /
• pp.92-99
• /
• 2009

This paper established the range of the wavelength of traffic lights to detection the color of traffic lights and the color component segmentation with the range of the wavelength. Development of traffic light automatic discrimination system is consists of the color detection and the traffic lights recognition. In this thesis, it established the range of the wavelength of traffic lights to detection the color of traffic lights and the color segmentation with the range of the wavelength. By the segmentation, the traffic light colors(red, orange and green) can be detected and the background is changed into gray image. Next, we proposed the algorithm which can detect the area of traffic lights in the various surroundings with the wavelet transformation algorithm. Also, we proposed traffic lights recognition algorithm using between the edge operator and the Hausdorff distance algorithm based on CBIR(Content-based Image retrieval). Therefore, the proposed algorithm is more superior to the conventional algorithm by experimenting with the illumination including the traffic lights and the backgrounds with various images.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.588-591
• /
• 2004

In this paper, we propose a ground plane detection algorithm, using a new image processing method (IPD). To extract the ground plane from the color image acquired by monocular camera, we use a new identical pixel detection method (IPD) and an edge detection method. This IPD method decides whether the pixel is identical with the ground plane pixel or not. The IPD method needs the reference area and its performance depends on the reference area size. So we propose the reference area auto-expanding algorithm in accordance with situation. And we evaluated the proposed algorithm by the experiments in the various environments. From the experiments results, we know that the proposed algorithm is efficient in the real indoor environment.

• Journal of Sensor Science and Technology
• /
• v.29 no.2
• /
• pp.133-140
• /
• 2020

This study proposes a method of blending visible and near infrared images to enhance edge details and local contrast. The proposed method consists of radiance map generation and color compensation. The radiance map is produced by a Laplacian pyramid and a soft mixing method based on principal component analysis. The color compensation method uses the ratio between the composed radiance map and the luminance channel of a visible image to preserve the visible image chrominance. The proposed method has better edge details compared to a conventional visible and NIR image blending method.

• Korean Management Science Review
• /
• v.13 no.2
• /
• pp.1-11
• /
• 1996

Two different methods to extract the license plate area of a vehicle have been used for automatic recognition purposes. One method is with a color vision system and the other is with an edge detecting operator. The system with color vision has some problems if the colors of license plate and vehicle's body are similar. The various plate colors in Korea also drops the system performance. The edge detecting operator also has a problem for a real time processing since it performs on all pixels of the scene. In this paper a possible method using gray level vision system and available pre-known information of license plates is suggested. The suggested procedure searches the lower boundary of the plate by counting high contrast points between one and near pixel from the bottom line of the scene. It finds the upper boundary from the bottom line by adding number plate height after finding the lower boundary. The left and right boundaries are found by similar processes.

• Journal of applied mathematics & informatics
• /
• v.19 no.1_2
• /
• pp.127-133
• /
• 2005

An f-coloring of a graph G = (V, E) is a coloring of edge set E such that each color appears at each vertex v $\in$ V at most f(v) times. The minimum number of colors needed to f-color G is called the f-chromatic index $\chi'_f(G)$ of G. Any graph G has f-chromatic index equal to ${\Delta}_f(G)\;or\;{\Delta}_f(G)+1,\;where\;{\Delta}_f(G)\;=\;max\{{\lceil}\frac{d(v)}{f(v)}{\rceil}\}$. If $\chi'_f(G)$= ${\Delta}$f(G), then G is of $C_f$ 1 ; otherwise G is of $C_f$ 2. In this paper, the classification problem of complete graphs on f-coloring is solved completely.

• Proceedings of the IEEK Conference
• /
• 2006.06a
• /
• pp.277-278
• /
• 2006

Recently, as development of technique about super highway network and multimedia, the technique which effectively transfers, manages, stores and retrieves multimedia data is influenced. In this paper, by using HMMD color model and edge Histogram for segmentation of movie, efficient video segmentation is implemented than existing technologies.

• IEIE Transactions on Smart Processing and Computing
• /
• v.2 no.4
• /
• pp.189-196
• /
• 2013

This paper presents a two-stage approach to detect pedestrians in video sequences taken from a moving vehicle. The first stage is a preprocessing step, in which potential pedestrians are hypothesized. During the preprocessing step, a difference image is constructed using a global motion estimation, vertical and horizontal edge maps are extracted, and the color difference between the road and pedestrians are determined to create candidate regions where pedestrians may be present. The candidate regions are refined further using the vertical edge symmetry features of the pedestrians' legs. In the next stage, each hypothesis is verified using the integral channel features and an AdaBoost classifier. In this stage, a decision is made as to whether or not each candidate region contains a pedestrian. The proposed algorithm was tested on a range of dataset images and showed good performance.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.251-252
• /
• 2007

The thesis proposed the Text Extraction Algorithm which is a text extraction algorithm which uses the Coiflet Wavelet, YCbCr Color model and the close curve edge feature of adaptive LoG Operator in order to complement the demerit of the existing research which is weak in complexity of background, variety of light and disordered line and similarity of text and background color. This thesis is simulated with natural images which include naturally text area regardless of size, resolution and slant and so on of image. And the proposed algorithm is confirmed to an excellent by compared with an existing extraction algorithm in same image.

• Journal of Information Processing Systems
• /
• v.16 no.6
• /
• pp.1479-1494
• /
• 2020

As an important part of image processing, image demosaicking has been widely researched. It is especially necessary to propose an efficient interpolation algorithm with good visual quality and performance. To improve the limitations of residual interpolation (RI), based on RI algorithm, minimalized-Laplacian RI (MLRI), and iterative RI (IRI), this paper focuses on adaptive RI (ARI) and proposes an improved ARI (IARI) algorithm which obtains more distinct R, G, and B colors in the images. The proposed scheme fully considers the brightness information and edge information of the image. Since the ARI algorithm is not completely adaptive, IARI algorithm executes ARI algorithm twice on R and B components according to the directional difference, which surely achieves an adaptive algorithm for all color components. Experimental results show that the improved method has better performance than other four existing methods both in subjective assessment and objective assessment, especially in the complex edge area and color brightness recovery.