Video-based Dynamic Mesh Coding (V-DMC), being standardized by the MPEG-3DGH group, seeks to establish an efficient standard for compressing dynamic meshes with time-varying vertex positions, connectivity, and attributes. By adopting a subdivision and video-based framework, V-DMC effectively leverages both advanced static mesh and video codecs, achieving state-of-the-art dynamic mesh coding efficiency. However, in V-DMC, inter-frame coding—one of the key coding tools—is applied only to a limited subset of frames and remains computationally expensive. To overcome this limitation, we propose a novel inter-frame coding framework for V-DMC that extends applicability to a much larger portion of frames while achieving both high efficiency and low complexity. Specifically, our method consists of four modules: (a) supervoxel-based shape matching for robust and efficient motion estimation; (b) embedded graph deformation for accurate geometry tracking; (c) early interframe coding mode decision for accelerated rate-distortion optimization; and (d) UV atlas tracking for generating temporally consistent texture images. Experimental results on the MPEG dynamic mesh dataset show that the proposed method achieves BD-rate improvements of −10.1%, −10.1%, −14.7%, −17.6%, and −15.5% for D1, D2, Luma, Cb, and Cr, respectively, along with a 5% decrease in encoding runtime compared to V-DMC reference software.

The MPEG-3DGH group is developing a new standard for dynamic mesh encoding, known as Video-based Dynamic Mesh Coding (V-DMC). One of the main challenges in the V-DMC encoding process is extracting temporally corresponding information required for the inter-frame coding when dealing with inputs that have time-varying connectivity. To provide an efficient and effective solution, we propose a fast supervoxel-based base mesh generation method complient with V-DMC inter-frame coding. Our method includes four steps: 1) Initial supervoxel segmentation on two given frames; 2) Supervoxel-based shape matching to extract an initial correspondence set; 3) Refined supervoxel segmentation and shape matching with the assistance of the initial correspondence set, which outputs a refined correspondence set with more correspondence vertices and higher accuracy; 4) Generation of inter-frame base meshes using the refined correspondence set. Experiments on the MPEG V-DMC test sequences demonstrate that our method achieves BD-rate improvements over the VDMC v6.0 in terms of D1, D2, Luma, Cb, and Cr metrics by -9.2%, -9.3%, -14.1%, -14.6%, and -9.7%, respectively. Additionally, the proposed method only increases the encoding time from 100% to 105% while suppressing the decoding time from 100% to 99%.

Merge mode has been utilized in advanced video coding standards to facilitate the efficiency of Motion vector (MV) or Block Vector (BV) coding. Merge mode constructs multiple MVs or BVs as the merge candidate list from MV/BV storage and then specifies one within the list by signaling the merge index. Despite various merge candidate derivation methods in prior arts, they do not adequately reach MV/BV, pointing to reference pictures with low quantization noise, leaving room for improved coding performance. This paper proposes a Chained Motion Vector Prediction (CMVP) as a novel merge candidate derivation. The CMVP derives new candidates by accumulating the recursively traced MVs or BVs based on pre-derived merge candidates. Experimental results demonstrate that the proposed method achieves up to 1.01% coding gains with negligible complexity increases on version 12 of Enhanced Compression Model (ECM), a reference software for evaluating promising coding tools beyond Versatile Video Coding (VVC).

The MPEG-3DGH group is developing a new standard for dynamic mesh encoding, known as Video-based Dynamic Mesh Coding (V-DMC). While V-DMC leverages a base mesh framework to exploit temporal correlations in the geometry, it does not account for extracting temporal information during UV atlas generation. To extend the efficiency of UVAtlas from single-frame to multi-frame scenarios, we propose a temporally consistent UVAtlas generation method compatible with V-DMC. Our method begins by applying keypoint tracking to capture the motion of the input sequence. Next, we perform patch partitioning and mapping to ensure consistent patches across frames. Each patch is then parameterized by minimizing geodesic distance distortion. Finally, all matched patches are packed into the same position within the texture domain. Our approach successfully generates consistent texture maps across an entire GOF (Group of Frames), significantly reducing the texture bitrate. Experimental results on the MPEG V-DMC test sequences demonstrate that our method achieves significant BD-rate improvements over the anchor of −13.9%, −13.9%, −10.6%, −14.5%, and −12.0% for D1, D2, Luma, Cb, and Cr PSNR metrics, respectively.

The Video-based Dynamic Mesh Coding (V-DMC), currently under development by the MPEG-3DGH group, employs a simplification and approximation framework for geometry coding. First, the input mesh is simplified into a base mesh with fewer faces, edges, and vertices. The base mesh is then subdivided and deformed to approximate the original mesh, with the offsets between the subdivided mesh and the deformed mesh referred to as displacements. Optimizing both the base mesh and the deformed mesh is crucial to achieving high coding quality. This process is termed geometry parametrization in V-DMC. In this paper, we propose a stabilization method for geometry parametrization in V-DMC to ensure robust results. Experimental results on the MPEG VDMC test sequences show that our method not only enhances the numerical stability of the geometry parametrization process but also improves quantitative coding performance and visual quality. Specifically, our method achieves BD-rate improvements over the anchor of -0.2%, -0.2%, -0.2%, -0.2%, and -0.2% for D1, D2, Luma, Cb, and Cr PSNR metrics, respectively. The proposed method has been adopted and integrated into the MPEG V-DMC reference software.

Multi-resolution functionality is a powerful tool in video content delivery services, ensuring compatibility across various devices and optimizing bandwidth usage. However, 3D Gaussian Splatting (3DGS), an explicit radiance field for new view synthesis and efficient rendering, currently lacks such functionality. This paper introduces multi-resolution functionality for 3DGS for the first time. Recognizing that the number of 3D Gaussians is a critical factor influencing resource consumption in 3DGS rendering, we propose a method to control this number across various resolutions. We propose a novel pyramidal data structure called Multi-Res-3DGS, which binds 3D Gaussians with a sequence of subdivided meshes. In this framework, the pyramidal meshes guide the multi-resolution through iterative subdivision, while the 3D Gaussians encode details associated with the mesh faces. The Multi-Res-3DGS can be trained using a combination of existing techniques and rendered at the best resolution according to the available resources. Evaluations using the NeRF-Synthetic dataset demonstrate that our approach realizes the multi-resolution functionality with minimal PSNR or LPIPS losses.

The Video-based Dynamic Mesh Coding (V-DMC) standard exploits the temporal correlation by tracing the motions of the vertices, which applies only to tracked frames with one-to-one vertex correspondence. For non-tracked frames, only intra mode is applied. This paper proposes an embedded graph representation method that can efficiently represent inter-frame differences for both tracked and non-tracked frames. First, we construct an embedded graph by simplifying the given mesh. Then, we compute a set of affine transformations on graph nodes and use their linear combinations to represent the inter-frame difference. Finally, we apply our implementation to increase the number of predicted frames (P-frames) and thus improve the resulting coding performance. Evaluations on Moving Picture Experts Group (MPEG) test sequences demonstrate the significant rate distortion improvements achieved by our method over V-DMC. The proposed method is highly compliant with V-DMC, and a part of it has been adopted into the V-DMC reference software during the MPEG-3DGH 144th meeting.

The MPEG-3DGH group is advancing a new standard for dynamic mesh encoding, known as Video-based Dynamic Mesh Coding (V-DMC). While V-DMC improves efficiency by toggling between intra- and inter-frame coding, it struggles with dynamic meshes that change inconsistently across frames. To address this issue, we introduce a novel partial inter-frame coding mode within the V-DMC framework. The method initiates by partitioning the adjacent frames into temporally aligned segments. These segments are then classified as suitable for either intra-frame or inter-frame coding based on the detection of inconsistent changes. Leveraging these segmentations, we introduce a partial inter-frame coding mode that allows for the selective application of intra- and inter-frame coding at the level of individual segments. Experiments on the MPEG V-DMC test sequences demonstrate that our method can achieve BD-rate improvement over the anchor in terms of D1, D2, Luma, Cb, and Cr PSNRs by -2.1%,-2.7%,-4.7%,-5.4%, and -4.5%, respectively.

In this paper, we propose an extended multimodel cross-component linear model (MMLM) for video compression beyond the versatile video coding standard. Our proposed method incorporates adaptive thresholding and overlapped averaging to enhance prediction accuracy and reduce discontinuities in multiple linear models. We evaluate our method’s coding gain on various video sequences and demonstrate a notable improvement of up to 1.3% bit-rate savings over the conventional MMLM, validating our method’s efficiency in high-efficiency video compression.

Intra block copy (IBC), an intra coding tool with a single block vector (BV), has been exploited for significant coding gains of screen content (SC) in advanced video coding standards such as VVC. Several studies have applied IBC to camera-captured content (CC), such as the IBC with fractional-sample-precision BV, which was adopted into the reference software for exploring beyond VVC, i.e., the enhanced compression model (ECM). However, there is room to further achieve the coding gains of IBC because all the conventional methods are uni-predictive IBC with a single BV to generate prediction samples. This paper proposes a bi-predictive IBC using two BVs as a new IBC algorithm for CC and SC, realized by extending the number of BVs in BV storage. In addition, this paper proposes encoder early terminations of applying IBC for CC by comparing coefficients and distortions of the IBC and intra prediction to avoid encoder runtime increases while maintaining coding gains. Experimental results show that the proposed method brings $0.15 \%$ and $0.30 \%$ coding gains for CC and SC over ECM-9 under all-intra configuration, with negligible complexity increases. The proposed method has been adopted into ECM-10.

The video-based dynamic mesh coding (V-DMC) standard is a cutting-edge technology for the compression of dynamic mesh data. V-DMC enables parallel encoding and partial decoding by introducing submesh frameworks in which dynamic meshes are separated and independently processed. However, V-DMC may raise submesh boundary errors like holes due to misaligning the existence or coordinates of vertices, degrading the objective and subjective qualities of decoded dynamic meshes. To minimize the boundary errors and improve the coding performance, we propose a two-stage boundary error correction method in V-DMC’s preprocessing and encoding/decoding stages. Specifically, the first stage rearranges the preprocessing order to minimize boundary errors, whereas the second stage fills holes based on boundary information. Experimental results show that the proposed method can minimize the boundary errors among the V-DMC decoded meshes, and thus significantly improve the objective and subjective quality compared to the V-DMC reference software.

Dynamic meshes reasonably represent time-varying 3D objects, but compression is required due to the large amount of data involved. One efficient framework decomposes a dynamic mesh into a base mesh and displacements using decimation and subdivision. The displacements are converted to levels by wavelet transforms and quantization, and they are coded by arithmetic coding. The levels of the current frame are predicted from the reference frame, and only the residuals are coded. However, quantization errors occur two times in the reference frame and the current frame since the coefficients of each frame are quantized before performing inter prediction. In this paper, we propose a method of quantizing the residuals obtained after applying inter prediction in order to reduce the amount of required data. The experimental results show that the proposed method yields improved coding efficiency and that the reconstructed mesh has no quality degradations.

This paper presents the first implementation of temporal scalability in the ongoing standard for Video-based Dynamic Mesh Coding (V-DMC), a crucial enhancement that enables bitstream adaptation to diverse network conditions and device capabilities. While displacement and texture, two of the V-DMC’s sub-bitstreams, already benefit from existing video codec temporal scalability, the non-video basemesh sub-bitstream lacks this feature. To address this gap, we propose an adaptive coding structure designed for the basemesh. Moreover, we propose a novel cost function to adaptively select the frame type between intra-frame and inter-frame in this coding structure. Our experimental results demonstrate significant improvements in coding efficiency compared to the original V-DMC, i.e., the total BD-rates of D1, D2, Luma, Cb, and Cr averaged across all eight test sequences are -15.1%, -15.0%, 0.3%,-9.9%, and -8.4 %, respectively.

This paper introduces an advanced intra prediction method designed for the Enhanced Compression Model (ECM), which is the reference software for beyond versatile video coding (VVC) standard. It employs a learning-based method to adaptively assign weights for a weighted average across neighboring samples, resulting in more precise prediction samples. The proposed method derives optimized weights for each intra prediction mode, for each block size, and for each sample position. To achieve a reasonable balance between encoding time and prediction accuracy, the conventional intra prediction mode is shared with the proposed method. Experimental evaluations have demonstrated that the proposed method provides bitrate reduction of up to 0.4%.

Standardization of Dynamic Mesh Coding (V-DMC) has been progressing in MPEG since 2022. The current reference software for V-DMC encodes dynamic meshes by segmenting them into regions (submeshes) and correcting holes occurring at submesh boundaries based on submesh boundary information. However, the encoding performance of submesh boundary information is low in V-DMC because it does not utilize the temporal correlation of submesh boundary information. To address this issue, we propose an inter-coding method for submesh boundary information using reference frame submesh boundary information. Experimental results show that our proposal improves coding performance compared to conventional methods.

Video-based Dynamic Mesh Coding (V-DMC) is an emerging standard for dynamic mesh compression, where the original meshes are decimated into simplified meshes called base meshes. This paper introduces a novel SKIP type for base mesh coding in V-DMC, complementing the existing INTRA and INTER types. When the SKIP type is used in base mesh coding, it directly copies the reconstructed base mesh from the reference frame, eliminating the need for additional data coding. Thus, the reconstructed base mesh in the current frame is identical to that in the reference frame. This significantly reduces the bit rate and decoding time for base meshes. Additionally, this paper employs a Lagrangian cost function using a linear model for bit estimation of INTRA type and L1 norms for distortion approximation of SKIP type to enable the encoder to select the best type for base meshes. Experimental results demonstrate superior BD-rate performance and significantly reduced decoding time for base meshes using the SKIP type, particularly in sequences with minimal object movements.

Triangle soup (Trisoup) is being studied as a new coding tool for Geometry-based Point Cloud Compression (G-PCC) stan-dardized in the Moving Picture Experts Group (MPEG). Outside of MPEG, a variable-node-size extension of Trisoup is studied to increase the flexibility of G-PCC. A primary advantage of variable node size is to achieve better coding performance by selecting appropriate node size according to local geometric complexity and required bits. However, the node size is not optimized in terms of bit rate and distortion in the conventional extension. To maximize the coding performances of the variable-node-size method, we propose a new cost function considering both bit rates and distortions. The experimental results show that the proposed method provides -1.5 % coding performance improvement in point-to-point PSNR versus bit rate against the conventional extension.

The inter-frame coding of dynamic meshes with time varying topology is still under development in the current Video-based Dynamic Mesh Coding (V-DMC) standard. To address this issue and improve the coding efficiency, we propose a temporally-consistent re-meshing method. In particular, we introduce a robust inter-surface mapping framework to re-mesh the input meshes so that they have one-to-one vertex and face correspondence. Then, we simultaneously decimate the re-meshed input meshes to generate temporally-consistent base meshes, which is a key requirement for applying inter-frame coding in V-DMC. The evaluations on Moving Picture Experts Group (MPEG) test sequences demonstrate that our method can achieve rate-distortion performance superior to that of V-DMC.

Dynamic meshes reasonably represent time-varying 3D objects, but compression is required due to the large amount of data. One compression framework decomposes a dynamic mesh into a base mesh and displacements by using decimation and subdivision. The displacements are converted to coefficients by wavelet transforms, quantized, and compressed by video codec, which is well disseminated. However, the abundance of tools in video codec is too complex for uncorrelated displacements. In this paper, we propose hierarchical arithmetic coding, dividing the coefficient levels into blocks and smaller subblocks. When all levels are zero in a block/subblock, a flag is coded instead of the levels. The experimental results show that the coding complexity was significantly reduced while the coding efficiency was maintained.

Next-generation video coding standards are attempting to improve coding performance compared to conventional standards such as VVC by extending technologies such as intra-block copy (IBC). While IBC in VVC has proven effective for screen content, its adaptation to camera-captured content presents challenges regarding sample fluctuations and the continuity of block boundaries. This paper proposes a novel approach to improve IBC performance for camera-captured content by combining adaptive filtering (F-IBC) and overlapped block averaging (OB-IBC). The F-IBC filters IBC prediction samples using filter coefficients derived from adjacent samples to predict sample fluctuations accurately. The OB-IBC is a weighted average of IBC prediction samples of the current block with adjacent samples of the adjacent block’s reference to connect block boundaries smoothly. Following common test conditions in the joint video experts team, experimental results show improved coding performance with a bitrate saving of 0.1 % over the reference software (ECM 7.0) which investigates the enhanced compression beyond VVC capability.

Compression of a dynamic mesh, which represents the dynamic volumetric data for immersive applications, is an emerging technique. One advanced compression technique is video-based dynamic mesh coding (V-DMC). Therein, an original mesh is decomposed into a decimated base mesh including displacement vectors in the V-DMC framework. Because the mesh represents an object in 3D space, these displacements, which express the detailed information of the mesh, are also represented as 3D vectors over the subdivision surface. However, such representation of a 3D vector is redundant because the displacement direction is almost equal to a normal direction of the subdivision surface. Hence, we present a 1D displacement coding that operates with an existing video codec. This method improves both the encoding/decoding procedure complexity and the coding performance on dynamic mesh coding when compared to competing approaches.

Dynamic meshes reasonably represent time-varying 3D objects, but compression is required due to the large amount of data. One efficient framework decomposes a dynamic mesh into a base mesh and displacements using decimation and subdivision. The displacements are converted to levels by wavelet transforms and quantization, and the levels are coded by block-based hierarchical arithmetic coding. However, the coding complexity is high in the worst case where all coefficients are encoded. In this paper, we propose arithmetic coding of levels with a bypass mode, which has low complexity by skipping context updates. The experimental results show that the coding complexity in the worst case was reduced while coding efficiency was maintained.

Relative viewpoint estimation is a fundamental problem in various image processing applications. Traditional estimation approaches can fail if sufficient appearance overlap is not observed between two images. Recent advances in 3D representation learning from images have made it possible to exploit the underlying 3D structure. In this paper, we propose a relative viewpoint estimation method using an end-to-end trainable network that learns structured 3D representations. In the proposed method, an independent coordinate system is set for each image in order to construct a structured 3D representation. This makes it possible to estimate the relative viewpoint by aligning those representations through coordinate transformations. Experimental results on the ShapeNet, Pix3D, and Thingi10K datasets demonstrated that the proposed method achieves accurate estimation even if there is not sufficient observable appearance overlap between the images.

In order to improve coding efficiency beyond versatile video coding (VVC), we propose an extended geometric partitioning mode (GPM). GPM is a new inter prediction in VVC and is applied to the object boundary between the foreground and background with different motions. Specifically, GPM partitions a rectangular coding block into two regions with 64 predefined types of straight lines, generates inter prediction samples for each partitioned region and then blends them with a fixed boundary width to obtain the final prediction samples. However, the fixed boundary width of GPM is not always optimal for diverse video content. To solve this problem, the proposed method allows GPM to select multiple boundary widths by block-wise signaling. Furthermore, the proposed method also restricts the selectable boundary width according to the short side of the block to reduce the encoding time for selecting the optimal width. Experiment results following common test conditions in JVET showed an improvement in coding efficiency with bitrate savings of 0.11 % and 3.20 % for camera-captured content and for pure screen or video game content, respectively, compared VVC reference software.

We previously proposed a novel lossless coding method that utilizes example search and adaptive prediction within a framework of probability model optimization for monochrome video. In this paper, we improve the adaptive prediction in terms of coding performance and processing time. More precisely, we made modifications to the following three items: (a) reference pel arrangements, (b) motion vector derivation, and (c) optimal selection of predictors. Experimental results show that the proposed method certainly improves the coding performance and the processing time compared to our previous method, and achieves better coding performance than the VVC-based lossless video coding scheme.

Overlapped block motion compensation (OBMC) is one of the inter prediction tools that improves coding performance. OBMC applied to various non-squared blocks has been studied in VVC, which is being standardized by joint video experts team (JVET), to improve coding performance over HEVC. Memory bandwidth, however, is a bottleneck when OBMC is used, and conventional methods have not achieved a good trade-off regarding coding performance and memory bandwidth so far. In this study, interpolation filters and applicable conditions of OBMC depending on block sizes are proposed to achieve the best trade-off. The experimental results show a -0.40% BD-rate gain compared with that of the VVC test model 3 for random access conditions under the common test condition in JVET.

A reduced balance ability can lead to falls and critical injuries. To prevent falls, humans use reaction forces and torques generated by swinging their arms. In animals, we can find that a similar strategy is taken using tails. Inspired by these strategies, we propose an approach that utilizes a robotic appendage as a human balance supporter without assistance from environmental contact. As a proof of concept, we developed a wearable robotic appendage that has one actuated degree of freedom and rotates around the sagittal axis of the wearer. To validate the feasibility of our proposed approach, we conducted an evaluation experiment with human subjects. Controlling the robotic appendage we developed improved the subjects' balance ability and enabled the subject to withstand up to 22.8 % larger impulse disturbances on average than in the fixed appendage condition.

Intra interpolation filters for intra angular prediction play an important role in the coding performance. In the intra angular prediction of VVC, which is being standardized by the joint video coding expert team (JVET), block-size based switchable interpolation filters between 4-tap cubic and Gaussian interpolation filters is being studied. Although the two filters have different frequency characteristics, block size-based criteria are insufficient to represent the reference sample characteristics. In this manuscript, switching criteria based on both the block-size and QP value are proposed to improve the coding performance. The experimental results show a -0.45% BD-rate gain compared with that by the VVC test model 2 for all intra conditions under the common test condition (CTC) in JVET.

In this paper, we propose an explicit residual decorrelation method to improve the coding performance for 4:4:4 chroma format conforming HEVC framework. The energy from a residual signal is gathered to the primary component by decorrelation of color space. The transform matrix as decorrelation is derived from reference pixel value by using singular value decomposition for each prediction unit. Since the derivation is applied in both encoder and decoder side, the identical matrix is obtained for both sides. Compared to the previous works, the proposed method applies only for the meaningful unit while an enabled flag is explicitly signaled as side information. The proposed method is implemented on HEVC test model. For the RGB/YUV 4:4:4 chroma format sequences, the coding gains in BD-rate are up to 23.3%/4.9%, respectively. Compared to the result by the previous works, average gains are slightly decreased, while each gain of sequence is always better than that by conventional method.

Inter colour-component correlation is generally very high in RGB 4:4:4 chroma format. To improve the coding performance of the high efficiency video coding (HEVC) especially for such content, we propose the in-loop colour-space-transform. The colour space is dynamically transformed into un-correlated space by employing singular value decomposition (SVD) for each block at both the encoder and decoder. Signals in transformed colour space are coded with the existing intra / inter coding framework. We utilize the simplified SVD process implemented only by integer operations for the complexity reduction. Compared with HM10.0 as an anchor method, BD-bitrate gain reached 23.8% and 23.4% for the all intra case and the random access case, respectively, while a runtime of the decoder increase 4.8-9.8%.

HEVC (High Efficiency Video Coding) is an ongoing standardization target as the next generation of video compression technology. HEVC employs a coding tree block, which is a quad-tree structure of a coding unit. It also employs some unit types; coding unit, prediction unit, and transform unit. A coding unit can be divided into smaller units as prediction units. Though an asymmetric unit is used for inter coding, only symmetric units are permitted for intra coding. In this paper, we propose an asymmetric partitioning with a non-power-of-two transform as a prediction and transform unit. While conventional partitioning locates the cross-point of partitioning lines at the center of the coding unit, the proposed method locates the cross-point in places except center. The proposed method reduces 2.0% BD-bitrate compared with HM5.0 under all intra / high efficiency condition. The validity of the proposed method is confirmed by some experimental results.

Vector representation of binary images has an advantage of keeping high image quality for arbitrary scaling as well as editing capability of an object. However, the vector representation suffers from low compression efficiency compared with JBIG. In this paper, we show the main cause reducing coding efficiency and propose two methods to improve it. The proposed methods can reduce the file size of a binary image up to about 30-40 percent.

The major advantage of vector representation of an image is that the image quality is maintained for arbitrary scaling. In recent years, a demand for scalable image coding has been increasing because of the wide variety of available digital contents and display terminals. Conventional scalable coding schemes are based on raster representation, and thus, line drawings deteriorate in quality when expanded and shrunk. In this paper, we propose an edge reconstruction method using vector representation for the purpose of keeping a consistent spatial scalability on transmission and display. We take an anti-aliasing into account in edge areas for approximation of luminance values around the edge. The proposed method can improve PSNR by up to 2 dB as compared to the conventional methods when image is expanded and shrunk

In this paper, we propose a method to vectorize comic images including halftone dots. Our method can prevent the jaggy and moire phenomena when the images are enlarged and shrank. The method contains three modules: halftone dots separation, gradation approximation, and vectorization. At the first module, small isolated areas and altered areas by dilation and erosion operations are separated into halftone dots images. At the second module, areas of halftone are approximated by contours and gradation parameters. At the last module, both halftone areas and line drawings are vectorized and approximated by smooth contours. The size of compressed file produced by our method is equal or smaller than JBIG compression. Validity of the proposed method is confirmed by experimental results.

Vector representation of graphics has the advantage that the image can be displayed at any size. When the resolution of a bitmap image is changed, the lack of a line segment arises. In addition, moire occurs when the resolution of an image with halftone dots is changed. We propose a new technique to convert a binary image with halftone dots into its vector representation. Resolution conversion of a binary image can easily be performed without moire by using a continuous tone approximation of the halftone dots. First, we separate the area of halftone dots and line drawings in the image. Next, a continuous tone approximation is applied to the area of halftone dots. Then, conventional vectorization is applied to both continuous tone areas and line drawings. Finally, these components are mixed and reconstructed. Our approach provides an efficient way of displaying cartoon-like images at any size with a limited amount of data.