Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631621
Zongyu Zhang, Chengwei Zhou, Yujie Gu, Zhiguo Shi
In this paper, we present a fast Fourier transform (FFT)-based direction-of-arrival (DOA) estimation algorithm for coprime multiple-input multiple-output (MIMO) radar, where both the performance and the system overhead are well balanced. The coprime arrays are deployed in the framework of MIMO radar for sparse sensing, where an augmented virtual array can be generated from the difference coarray of sum coarray (DCSC) perspective. By implementing FFT on the second-order DCSC signals, it is shown that the DOAs can be retrieved from the resulting spatial response with an improved resolution. Moreover, neither the complex matrix operations nor the optimization problems are involved, indicating the efficient and hardware-friendly characteristic. Simulation results demonstrate the performance superiorities of the proposed algorithm.
{"title":"FFT-Based DOA Estimation for Coprime MIMO Radar: A Hardware-Friendly Approach","authors":"Zongyu Zhang, Chengwei Zhou, Yujie Gu, Zhiguo Shi","doi":"10.1109/ICDSP.2018.8631621","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631621","url":null,"abstract":"In this paper, we present a fast Fourier transform (FFT)-based direction-of-arrival (DOA) estimation algorithm for coprime multiple-input multiple-output (MIMO) radar, where both the performance and the system overhead are well balanced. The coprime arrays are deployed in the framework of MIMO radar for sparse sensing, where an augmented virtual array can be generated from the difference coarray of sum coarray (DCSC) perspective. By implementing FFT on the second-order DCSC signals, it is shown that the DOAs can be retrieved from the resulting spatial response with an improved resolution. Moreover, neither the complex matrix operations nor the optimization problems are involved, indicating the efficient and hardware-friendly characteristic. Simulation results demonstrate the performance superiorities of the proposed algorithm.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125229088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631805
Sheng Zhang, W. Zheng
A multi-sampled multiband-structured sub-band adaptive filtering (MS-MSAF) algorithm is proposed in this paper. The key feature of the proposed algorithm lies in the expansion of the sub-sampled number to a common value. The properties of mean stability and mean-square deviation of the MS-MSAF algorithm are analyzed in the original time domain, and the theoretical analysis also leads to a way to accelerate the convergence speed of the proposed MS-MSAF algorithm. The obtained theoretical results are verified through computer simulations.
{"title":"A Multi-Sampled Multiband-Structured Subband Filtering Algorithm","authors":"Sheng Zhang, W. Zheng","doi":"10.1109/ICDSP.2018.8631805","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631805","url":null,"abstract":"A multi-sampled multiband-structured sub-band adaptive filtering (MS-MSAF) algorithm is proposed in this paper. The key feature of the proposed algorithm lies in the expansion of the sub-sampled number to a common value. The properties of mean stability and mean-square deviation of the MS-MSAF algorithm are analyzed in the original time domain, and the theoretical analysis also leads to a way to accelerate the convergence speed of the proposed MS-MSAF algorithm. The obtained theoretical results are verified through computer simulations.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124238075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631588
Ruofei Hu, Binren Tian, S. Yin, Shaojun Wei
Deep neural network (DNN), as a very important machine learning technique in classification and detection tasks for images, video, speech as wellas audio, has recently received tremendous attention. Integral Stochastic Computation (Integral SC), on the other hand, has proved its extraordinary ability in hardware implementation of DNNs. Thesoftmax layer is generally used in multi-classification tasks as a very basic and important network layer in DNNs. However, the hardware implementation of softmax layer is expensive cause the exponentiation and division computation. In this paper, we designed an efficient way to simulate softmax layer in DNNs based on Integral stochastic computing, filling the vacancy of previous academic works. Compared to conventional softmax hardware implementation, our method achieves reduction in power and area by 68% and 41%, respectively.
深度神经网络(Deep neural network, DNN)作为一种非常重要的机器学习技术，在图像、视频、语音和音频的分类和检测任务中得到了广泛的关注。另一方面，积分随机计算(Integral random Computation, SC)在深度神经网络的硬件实现中已经证明了其非凡的能力。oftmax层通常用于多分类任务中，是dnn中非常基础和重要的网络层。然而，softmax层的硬件实现开销很大，因为它需要进行乘除运算。本文设计了一种基于积分随机计算的深度神经网络中softmax层的有效模拟方法，填补了前人研究的空白。与传统的softmax硬件实现相比，我们的方法分别减少了68%和41%的功耗和面积。
{"title":"Efficient Hardware Architecture of Softmax Layer in Deep Neural Network","authors":"Ruofei Hu, Binren Tian, S. Yin, Shaojun Wei","doi":"10.1109/ICDSP.2018.8631588","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631588","url":null,"abstract":"Deep neural network (DNN), as a very important machine learning technique in classification and detection tasks for images, video, speech as wellas audio, has recently received tremendous attention. Integral Stochastic Computation (Integral SC), on the other hand, has proved its extraordinary ability in hardware implementation of DNNs. Thesoftmax layer is generally used in multi-classification tasks as a very basic and important network layer in DNNs. However, the hardware implementation of softmax layer is expensive cause the exponentiation and division computation. In this paper, we designed an efficient way to simulate softmax layer in DNNs based on Integral stochastic computing, filling the vacancy of previous academic works. Compared to conventional softmax hardware implementation, our method achieves reduction in power and area by 68% and 41%, respectively.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124478466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631543
Yang Zhou, Zisheng Wu, Xueling Zhou, B. Ling, Xiaozhu Mo, C. H. Li
This paper proposes to employ the discrete cosine transform (DCT) to perform the empirical mode decomposition (EMD) based hierarchical multiresolution analysis. This can simplify the implementation because all the signals are real valued. In this paper, the intrinsic mode functions (IMFs) in the first level of decomposition are obtained by applying the conventional EMD to an electrocardiogram (ECG). Then, the first IMF is further decomposed. More precisely, the zeros are inserted to the first IMF in the DCT domain. Then, the conventional EMD is applied to this zero inserted signal to obtain a new set of IMFs. Next, the DCT coefficients of the new set of IMFs where the zeros are inserted before are discarded. To perform the denoising and the QRS point enhancement, the first IMF in the second level of the decomposition is discarded. The rest of the IMFs in the second level of decomposition as well all the IMFs in the first level of decomposition except the first IMF in the first level of decomposition are summed together to obtain the processed signal. The computer numerical simulation results show that our proposed method can achieve significant improvements in terms of the denoising performance and the QRS point enhancement compared to the corresponding single level EMD based processing.
{"title":"EMD Based Hierarchical Multiresolution Analysis via DCT with Applications to ECG Denoising and QRS Point Enhancement","authors":"Yang Zhou, Zisheng Wu, Xueling Zhou, B. Ling, Xiaozhu Mo, C. H. Li","doi":"10.1109/ICDSP.2018.8631543","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631543","url":null,"abstract":"This paper proposes to employ the discrete cosine transform (DCT) to perform the empirical mode decomposition (EMD) based hierarchical multiresolution analysis. This can simplify the implementation because all the signals are real valued. In this paper, the intrinsic mode functions (IMFs) in the first level of decomposition are obtained by applying the conventional EMD to an electrocardiogram (ECG). Then, the first IMF is further decomposed. More precisely, the zeros are inserted to the first IMF in the DCT domain. Then, the conventional EMD is applied to this zero inserted signal to obtain a new set of IMFs. Next, the DCT coefficients of the new set of IMFs where the zeros are inserted before are discarded. To perform the denoising and the QRS point enhancement, the first IMF in the second level of the decomposition is discarded. The rest of the IMFs in the second level of decomposition as well all the IMFs in the first level of decomposition except the first IMF in the first level of decomposition are summed together to obtain the processed signal. The computer numerical simulation results show that our proposed method can achieve significant improvements in terms of the denoising performance and the QRS point enhancement compared to the corresponding single level EMD based processing.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121680415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631702
Fengzhi Pan, Huiliang Shang
Image alignment is usually the first move in modern image stitching pipeline; and utilizing a global homography to align two images is justified on the condition that only pure rotation concatenates two views or the whole scene is planar. Ghosting effects frequently happen because aforementioned condition is rarely satisfied in practice; so we propose adaptive local homographies to improve image alignment further based on as-projective-as-possible warp (APAP). Specifically, we introduce an adaptive inlier selection scheme for fitting local homographies while APAP adopts moving DLT to do this with improper global inliers, so our warp can be more ”local” than APAP while still globally projective. As experiments show our warp moderately outperforms APAP in alignment accuracy and deblurring especially in the case of large parallax, which leads to a powerful alternative to moving DLT with acceptable overhead.
{"title":"Enhacing Image Mosaicing with Adaptive Local Homographies","authors":"Fengzhi Pan, Huiliang Shang","doi":"10.1109/ICDSP.2018.8631702","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631702","url":null,"abstract":"Image alignment is usually the first move in modern image stitching pipeline; and utilizing a global homography to align two images is justified on the condition that only pure rotation concatenates two views or the whole scene is planar. Ghosting effects frequently happen because aforementioned condition is rarely satisfied in practice; so we propose adaptive local homographies to improve image alignment further based on as-projective-as-possible warp (APAP). Specifically, we introduce an adaptive inlier selection scheme for fitting local homographies while APAP adopts moving DLT to do this with improper global inliers, so our warp can be more ”local” than APAP while still globally projective. As experiments show our warp moderately outperforms APAP in alignment accuracy and deblurring especially in the case of large parallax, which leads to a powerful alternative to moving DLT with acceptable overhead.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131390796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631685
Wangqian Chen, Mo Huang, Xin Lou
In this paper, a design method based on interpolation technique is proposed to design narrow-band sparse FIR filters and centrosymmetric bandpass filters. The design method is realized by cascading a model filter with a masking filter. The model filter is first designed and then interpolated to generate the desired impulse response replica. A sparse masking filter is used to mask the extra unwanted passbands. Unlike the interpolated FIR filter technique, both subfilters are designed as sparse filters by multiplierless algorithms to improve the overall sparsity of the filter. Simulation results show that the proposed cascaded realization of FIR filters results a significant improvement of sparsity than the conventional direct form or transposed direct form. It is also shown that the proposed method generates sparser solutions than the interpolated FIR filter technique due to the sparse design of subfilters.
{"title":"Sparse FIR Filter Design Based on Interpolation Technique","authors":"Wangqian Chen, Mo Huang, Xin Lou","doi":"10.1109/ICDSP.2018.8631685","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631685","url":null,"abstract":"In this paper, a design method based on interpolation technique is proposed to design narrow-band sparse FIR filters and centrosymmetric bandpass filters. The design method is realized by cascading a model filter with a masking filter. The model filter is first designed and then interpolated to generate the desired impulse response replica. A sparse masking filter is used to mask the extra unwanted passbands. Unlike the interpolated FIR filter technique, both subfilters are designed as sparse filters by multiplierless algorithms to improve the overall sparsity of the filter. Simulation results show that the proposed cascaded realization of FIR filters results a significant improvement of sparsity than the conventional direct form or transposed direct form. It is also shown that the proposed method generates sparser solutions than the interpolated FIR filter technique due to the sparse design of subfilters.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131736793","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631618
A. Jiang, Qing Wang, Jing Shang, Xiaofeng Liu
Common spatial pattern (CSP) is widely used in brain-computer interfaces (BCIs) to extract features from the multichannel EEG signals. However, the CSP method easily overfits to the data of small training sets and its performance can be degraded by highly noisy and interference channels. Furthermore, more recording channels imply more processing and computation time in practical applications. To overcome these drawbacks, in this paper we propose a novel sparse CSP algorithm by introducing sparsity into spatial filters. The proposed method adopts $l_{1}$ norm as sparsity metric and constrains the ratio between variances of spatially filtered EEG signals of two classes larger than a specified threshold. To improve computational efficiency, an iterative approach based on general eigenvalue decomposition is further developed. The experimental results on 9 subjects from BCI competition datasets publicly available demonstrate that the proposed algorithm can achieve comparable classification accuracy even when the number of channels is small.
{"title":"Sparse Common Spatial Pattern for EEG Channel Reduction in Brain-Computer Interfaces","authors":"A. Jiang, Qing Wang, Jing Shang, Xiaofeng Liu","doi":"10.1109/ICDSP.2018.8631618","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631618","url":null,"abstract":"Common spatial pattern (CSP) is widely used in brain-computer interfaces (BCIs) to extract features from the multichannel EEG signals. However, the CSP method easily overfits to the data of small training sets and its performance can be degraded by highly noisy and interference channels. Furthermore, more recording channels imply more processing and computation time in practical applications. To overcome these drawbacks, in this paper we propose a novel sparse CSP algorithm by introducing sparsity into spatial filters. The proposed method adopts $l_{1}$ norm as sparsity metric and constrains the ratio between variances of spatially filtered EEG signals of two classes larger than a specified threshold. To improve computational efficiency, an iterative approach based on general eigenvalue decomposition is further developed. The experimental results on 9 subjects from BCI competition datasets publicly available demonstrate that the proposed algorithm can achieve comparable classification accuracy even when the number of channels is small.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128387093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631788
Shu-Min Liu, Chenyan Li, Sao-Jie Chen
This work presents the application of Blind Source Separation (BSS) Algorithms on Dual-band IR Spectrogram for breast cancer detection and tracing the effect of long-term chemotherapy for breast-cancer patients. We take Dual-band IR Spectrogram’s RAW Data as an input to the BSS algorithms. Integrated into the back-end processor of a Dual-band IR Sensor and Readout Circuit Platform, our Improved Neighbor-based BSS algorithm operated on Dual-band IR Spectrogram provides a better breast cancer detection. Considering the demarcating degree, our Improved Neighbor-based BSS algorithm is approximately 15% better than other algorithms. As to the correctness rate, our improved algorithm approximately increases 10% compared with other algorithms.
{"title":"Application of BSS Algorithms for Breast Cancer Detection","authors":"Shu-Min Liu, Chenyan Li, Sao-Jie Chen","doi":"10.1109/ICDSP.2018.8631788","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631788","url":null,"abstract":"This work presents the application of Blind Source Separation (BSS) Algorithms on Dual-band IR Spectrogram for breast cancer detection and tracing the effect of long-term chemotherapy for breast-cancer patients. We take Dual-band IR Spectrogram’s RAW Data as an input to the BSS algorithms. Integrated into the back-end processor of a Dual-band IR Sensor and Readout Circuit Platform, our Improved Neighbor-based BSS algorithm operated on Dual-band IR Spectrogram provides a better breast cancer detection. Considering the demarcating degree, our Improved Neighbor-based BSS algorithm is approximately 15% better than other algorithms. As to the correctness rate, our improved algorithm approximately increases 10% compared with other algorithms.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131165332","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631609
Yi Zhang, Jiesi Kang, Jinfu Wang, Yue Xiao, Su Hu
This paper is concerned with the channel estimation for orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) systems in the presence of time varying channels. Although the estimation of the channel state information (CSI) for OFDM-IDMA systems is investigated by current literatures in slow fading channels, the channel estimation in the context of fast fading environments remains a challenge, which focuses on a desired tradeoff between the amount of pilot symbols and CSI estimation accuracy. For alleviating the above problem, in this paper, we develop a class of data-aided channel estimation schemes based on the log-likelihood ratio(LLR) calculation at the receiver to track the channel variations for OFDM-IDMA systems. Simulation results demonstrate that the proposed data-aided channel estimation scheme offers substantial performance gain over its conventional counterparts especially in the high-mobility case.
{"title":"Data-Aided Channel Estimation for OFDM-IDMA Systems","authors":"Yi Zhang, Jiesi Kang, Jinfu Wang, Yue Xiao, Su Hu","doi":"10.1109/ICDSP.2018.8631609","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631609","url":null,"abstract":"This paper is concerned with the channel estimation for orthogonal frequency division multiplexing interleave division multiple access (OFDM-IDMA) systems in the presence of time varying channels. Although the estimation of the channel state information (CSI) for OFDM-IDMA systems is investigated by current literatures in slow fading channels, the channel estimation in the context of fast fading environments remains a challenge, which focuses on a desired tradeoff between the amount of pilot symbols and CSI estimation accuracy. For alleviating the above problem, in this paper, we develop a class of data-aided channel estimation schemes based on the log-likelihood ratio(LLR) calculation at the receiver to track the channel variations for OFDM-IDMA systems. Simulation results demonstrate that the proposed data-aided channel estimation scheme offers substantial performance gain over its conventional counterparts especially in the high-mobility case.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130949963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-11-01DOI: 10.1109/ICDSP.2018.8631861
R. T. Hsung, W. Y. Lam, E. Pow
In computer-aided design and manufacturing (CAD/CAM) for dentistry, the digital dentition model is usually acquired using intraoral scanner or impression model scanning before further processing. Both tooth shape and shade play important role in treatment planning for patient satisfaction with dental esthetics. However, most of current intraoral scanners cannot generate good enough color texture information. For impression model scanning, tooth shade is even lost when making impression. In the paper we consider the technique using the image-to-geometry registration method to map color intraoral photographs onto the virtual models. We investigate the automatic technique to accurately find correspondences of the digital model and the color intraoral photographs. This eliminates manual placement error of correspondence for the registration.
{"title":"Image to Geometry Registration for Virtual Dental Models","authors":"R. T. Hsung, W. Y. Lam, E. Pow","doi":"10.1109/ICDSP.2018.8631861","DOIUrl":"https://doi.org/10.1109/ICDSP.2018.8631861","url":null,"abstract":"In computer-aided design and manufacturing (CAD/CAM) for dentistry, the digital dentition model is usually acquired using intraoral scanner or impression model scanning before further processing. Both tooth shape and shade play important role in treatment planning for patient satisfaction with dental esthetics. However, most of current intraoral scanners cannot generate good enough color texture information. For impression model scanning, tooth shade is even lost when making impression. In the paper we consider the technique using the image-to-geometry registration method to map color intraoral photographs onto the virtual models. We investigate the automatic technique to accurately find correspondences of the digital model and the color intraoral photographs. This eliminates manual placement error of correspondence for the registration.","PeriodicalId":218806,"journal":{"name":"2018 IEEE 23rd International Conference on Digital Signal Processing (DSP)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134643800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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