• Journal of Information Processing Systems
• /
• v.19 no.2
• /
• pp.232-239
• /
• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.

• The Journal of the Korea Contents Association
• /
• v.16 no.7
• /
• pp.431-438
• /
• 2016

In this paper, we present an upsampling technique for depth map image using color and depth weights. First, we construct a high-resolution image using the bilinear interpolation technique. Next, we detect a common edge region using RGB color space, HSV color space, and depth image. If an interpolated pixel belongs to the common edge region, we calculate weighting values of color and depth in $3{\times}3$ neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.11B
• /
• pp.1320-1327
• /
• 2009

In stereoscopy using stereo camera system, the representative factors inducing stereoscopic depth distortions have been reported such as the inter camera distance, the convergence angle and the depth resolution. The image distance is just known to us as a factor related in optical system. In a point of view of depth distortion, it will be a factor inducing a stereoscopic depth distortion. In this paper, we focused on the proof of our opinion that the image distance is one of the weighted factors inducing depth distortion under orthostereoscopic condition.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.11
• /
• pp.626-633
• /
• 2003

Theoretical analysis of the depth measurement system with the use of a single camera and a rotating mirror has been done. A camera in front of a rotating mirror acquires a sequence of reflected images, from which depth information is extracted. For an object point at a longer distance, the corresponding pixel in the sequence of images moves at a higher speed. Depth measurement based on such pixel movement is investigated. Since the mirror rotates along an axis that is in parallel with the vertical axis of the image plane, the image of an object will only move horizontally. This eases the task of finding corresponding image points. In this paper, the principle of the depth measurement-based on the relation of the pixel movement speed and the depth of objects have been investigated. Also, necessary mathematics to implement the technique is derived and presented. The factors affecting the measurement precision have been studied. Analysis shows that the measurement error increases with the increase of depth. The rotational angle of the mirror between two image-takings also affects the measurement precision. Experimental results using the real camera-mirror setup are reported.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.10
• /
• pp.874-880
• /
• 2002

A number of techniques have been proposed for 3D display using view-difference of two eyes. These methods do not express enough reality like real world. The display images have to change according to the position of a viewer to improve reality. In this paper, we present an approach for generating intermediate image between two different view images by applying new image interpolation algorithm The interpolation algorithm is designed to cope with complex shapes. The proposed image interpolation algorithm generates rotated image about vertical axes by any angle from base images. Each base image that was obtained from CCD camera has an view-angle difference of $3^{\circ}C$, $5.5^{\circ}C$, $^{\circ}C$, $22^{\circ}C$, and $45^{\circ}C$. The proposed into mediate image generation method uses the geometric analysis of image and depth information through the block-based matching method.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.10 no.1
• /
• pp.81-90
• /
• 2010

This paper presents H.264 coding schemes for multi-view video using the concept of layered depth image(LDI) representation and efficient compression technique for LDI. After converting those data to the proposed representation, we encode color, depth, and auxiliary data representing the hierarchical structure, respectively, Two kinds of preprocessing approaches are proposed for multiple color and depth components. In order to compress auxiliary data, we have employed a near lossless coding method. Finally, we have reconstructed the original viewpoints successfully from the decoded approach that is useful for dealing with multiple color and depth data simultaneously.

• Journal of Korea Society of Industrial Information Systems
• /
• v.29 no.1
• /
• pp.125-133
• /
• 2024

In this paper, we propose a volume measurement method for an object based on depth image. The object volume is measured by calculating the object height and width in actual units through the depth image. The object area is detected through differences between the captured and background depth images. The volume of the 2×2 pixel area, formed by four adjacent pixels using the depth information associated with each pixel, is measured. The object volume is measured as the sum of the volumes for whole 2×2 areas in the object area. In simulation results, the average measurement error for the object volume is 2.1% when the distance from the camera is 60cm.

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.903-914
• /
• 2020

In this paper, we present a novel algorithm to generate a 3D model of patient-specific orbital implant, which is finally produced by the 3D printer. Given CT (computed tomography) scan data of the defective orbital wall or floor, we compose the depth image of the defect site by using the depth buffering, which is a computer graphics technology. From the depth image, we compute the 3D surface which fills the broken part by interpolating the points around the broken part. By thickening the 3D surface, we get the 3D volume mesh of the orbital implant. Our algorithm generates the patient-specific orbital implant whose shape is accurately coincident to the broken part of the orbit. It provides the significant time efficiency for manufacturing the implant with supporting high user convenience.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2013.10a
• /
• pp.635-636
• /
• 2013

In this research, a method that quantize the depth information to improve the quality of the intermediate view images when DIBR (Depth Image Based Rendering) is used. This paper specially describes the uniform quantization that divides the depth information equally and non-uniform quantization that allocates more depth information in certain areas to improve the quality of the area.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.12
• /
• pp.2927-2936
• /
• 2013

In this paper, we propose a noise reduction and hole removal algorithm in order to improve the quality of depth images when they are used for creating 3D contents. In the proposed algorithm, the depth image and the corresponding color image are both used. First, an intensity image is generated by converting the RGB color space into the HSI color space. By estimating the difference of distance and depth between reference and neighbor pixels from the depth image and difference of intensity values from the color image, they are used to remove noise in the proposed algorithm. Then, the proposed hole filling method fills the detected holes with the difference of euclidean distance and intensity values between reference and neighbor pixels from the color image. Finally, we apply a parallel structure of GPGPU to the proposed algorithm to speed-up its processing time for real-time applications. The experimental results show that the proposed algorithm performs better than other conventional algorithms. Especially, the proposed algorithm is more effective in reducing edge blurring effect and removing noise and holes.