• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.7
• /
• pp.2997-3017
• /
• 2020

With the advancement in the field of image processing, images are being processed using various image processing algorithms. Nowadays, many efficient content-aware image resizing techniques are being used to safeguard the prominent regions and to generate better results that are visually appealing and pleasing while resizing. Advancements in the new display device with varying screen size demands the development of efficient image resizing algorithm. This paper presents a survey on various image retargeting methods, comparison of image retargeting results based on performance, and also exposes the main challenges in image retargeting such as content preservation of important regions, distortion minimization, and improving the efficiency of image retargeting methods. After reviewing literature from researchers it is suggested that the use of the single operator in image retargeting such as scaling, cropping, seam carving, and warping is not sufficient for obtaining satisfactory results, hence it is essential to combine multiple image retargeting operators. This survey is useful for the researchers interested in content-aware image retargeting.

• Journal of Information Processing Systems
• /
• v.19 no.3
• /
• pp.275-288
• /
• 2023

Many image edge details are easily lost in the image denoising process, and the smooth image regions are prone to produce jagged. In this paper, we propose a wavelet-based image global k- singular value decomposition variational method to remove image noise. A layer of wavelet decomposition is applied to the noisy image first. Then, the image global k-singular value decomposition (IGK-SVD) method is used to remove the random noise of low-frequency components. Furthermore, a constructed variational denoising method (VDM) removes the random noise in the high-frequency component. Finally, the denoised image is obtained by wavelet reconstruction. The experimental results show that the proposed method's peak signal-to-noise ratio (PSNR) value is higher than other methods, and its structural similarity (SSIM) value is closer to one, indicating that the proposed method can effectively suppress image noise while retaining more image edge details. The denoised image has better denoising effects.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.6
• /
• pp.468-476
• /
• 2002

The confidence of information from image processing depends on the original image quality. Enhancing the confidence by an algorithm has an essential limitation. Especially, road images are exposed to lots of noisy sources, which makes image processing difficult. We, in this paper, propose a FNN (fuzzy-neural network) capable oi deciding the quality of a road image prior to extracting lane-related information. According to the decision by the FNN, road images are classified into good or bad to extract lane-related information. A CDF (cumulative distribution function), a function of edge histogram, is utilized to construct input parameters of the FNN, it is based on the fact that the shape of the CDF and the image quality has large correlation. Input pattern vector to the FNN consists of ten parameters in which nine parameters are from the CDF and the other one is from intensity distribution of raw image. Correlation analysis shows that each parameter represents the image quality well. According to the experimental results, the proposed FNN system was quite successful. We carried out simulations with real images taken by various lighting and weather conditions and achieved about 99% successful decision-making.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.14 no.2
• /
• pp.35-47
• /
• 2018

The 4th industrial revolution, digital image technology has developed beyond the limit of multimedia industry to advanced IT fusion and composite industry. Particularly, application technology related to HCI element algorithm in 3D image object recognition field is actively developed. 3D image object recognition technology evolved into intelligent image sensing and recognition technology through 3D modeling. In particular, image recognition technology has been actively studied in image processing using object recognition recognition processing, face recognition, object recognition, and 3D object recognition. In this paper, we propose a research method of human factor 3D image recognition technology applying human factor algorithm for 3D object recognition. 1. Methods of 3D object recognition using 3D modeling, image system analysis, design and human cognitive technology analysis 2. We propose a 3D object recognition parameter estimation method using FACS algorithm and optimal object recognition measurement method. In this paper, we propose a method to effectively evaluate psychological research techniques using 3D image objects. We studied the 3D 3D recognition and applied the result to the object recognition element to extract and study the characteristic points of the recognition technology.

• Journal of Information Processing Systems
• /
• v.14 no.3
• /
• pp.590-599
• /
• 2018

Multivariate finite mixture model is becoming more and more popular in image processing. Performing image denoising from image patches to the whole image has been widely studied and applied. However, there remains a problem that the structure information is always ignored when transforming the patch into the vector form. In this paper, we study the operator which extracts patches from image and then transforms them to the vector form. Then, we find that some pixels which should be continuous in the image patches are discontinuous in the vector. Due to the poor anti-noise and the loss of structure information, we propose a new operator which may keep more information when extracting image patches. We compare the new operator with the old one by performing image denoising in Expected Patch Log Likelihood (EPLL) method, and we obtain better results in both visual effect and the value of PSNR.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.3
• /
• pp.555-562
• /
• 2007

In order to display Bayer input stream received from CMOS image sensor to the display device, image signal processing must be performed. That is, the hardware performing the image signal processing for Bayer data is called ISP(Image Signal Processor). We can see real image through ISP processing. ISP executes functionalities for gamma correction, interpolation, color space conversion, image effect, image scale, AWB, AE and AF. In this paper, we obtained the optimum algorithm through software verification of ISP module for CMOS camera image sensor and described using VHDL and verified in ModelSim6.0a simulator. Also we downloaded into Xilinx XCV-1000e for the designed ISP module and completed the board level verification using PCI interface.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
• /
• 1999.06a
• /
• pp.147-155
• /
• 1999

The film thickness and shape of elastohydrodynamic lubrication is measured by optical interferometer, which is the most precise method for EHL film measurement. However the interpretation of the image pattern from optical viscometer is not easy for two-dimensional shape. A newly developed method of image processing makes it possible to evaluate the film thickness and shape in every point of contact region with two dimensional aspects. In this study, we captured film shape of EHL film from the monochromatic incident light with the Image processing method, which uses phase shift method, and obtained the image analysis method for gray level image in order to qualitatively evaluate film shapes.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.40-43
• /
• 1997

This paper presents a 3D object recognition method for generation of 3D environmental map or obstacle recognition of mobile robots. An active light source projects a stripe pattern of light onto the object surface, while the camera observes the projected pattern from its offset point. The system consists of a laser unit and a camera on a pan/tilt device. The line segment in 2D camera image implies an object surface plane. The scaling, filtering, edge extraction, object extraction and line thinning are used for the enhancement of the light stripe image. We can get faithful depth informations of the object surface from the line segment interpretation. The performance of the proposed method has demonstrated in detail through the experiments for varies type objects. Experimental results show that the method has a good position accuracy, effectively eliminates optical noises in the image, greatly reduces memory requirement, and also greatly cut down the image processing time for the 3D object recognition compared to the conventional object recognition.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.4
• /
• pp.309-314
• /
• 2015

In this study, an embedded ranging system based on a laser structured light image is developed. The distance measurement by the structured light image processing has efficient computation because the burdensome correspondence problem is avoidable. In order to achieve robustness against environmental illumination noise and real-time laser structured light image processing, a bandpass optical filter is adopted in this study. The proposed ranging system has an embedded image processor performing the whole image processing and distance measurement, and so reduces the computational burden in the main control system. A system calibration algorithm is presented to compensate for the lens distortion.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.5 no.2
• /
• pp.57-62
• /
• 1996

Basically, the idea underlying most edge-detection technique is the computation of a local derivative operator used for edge detection in gray level image. This concept can be easily illustrated with the aid of object which shows an image of a simple lilght on a dark background, Using the gray level profile along a horizontal scan line of the image. the first and second derivatives of it were acquired. This study is to develop an automatic measuring system based on the digital image processing which can be applied to the real time measurement of the characteristics of the ultra-thin thickness. The experimental results indicate that the developed automatic inspection can be applied in real situation.