The Experts below are selected from a list of 3609 Experts worldwide ranked by ideXlab platform
Fumihiko Saitoh - One of the best experts on this subject based on the ideXlab platform.
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High-speed Image Matching by Extracting Block Areas and Pixels Using Two-stage Genetic Algorithm.
Journal of The Japan Society for Precision Engineering, 2020Co-Authors: Fumihiko SaitohAbstract:The Normalized Correlation matching is a typical image processing method for industrial applications. However, the Normalized Correlation matching requires a large computational cost because all pixels in a template image are used for the matching process. This paper proposes a method to extract partial block areas and pixels in the template image that are effective for the image matching using the two-stage genetic algorithm. The experimental results show that the number of pixels for the image matching was reduced to 7.8% by the 1st stage genetic algorithm and reduced to 1.5% by the 2nd stage genetic algorithm. The processing time for the image matching was also reduced from 9.78 second to 0.87 second by the proposed method.
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High-speed Image Matching Using Partial Template Consisting of Plural Rectangular Areas Extracted by Genetic Algorithm
Ieej Transactions on Electronics Information and Systems, 2020Co-Authors: Keita Okada, Fumihiko SaitohAbstract:In Normalized Correlation matching, a template image is set by manual operation before the matching process. Namely, the contents and the size of a template image are determined by the human sense. This paper proposes a method to perform a high-speed Normalized Correlation matching by extracting plural partial areas automatically that is effective in the image matching. These extracted plural partial areas become the new template image. The proposed method extracts plural partial areas suitable for matching by genetic algorithm. The experimental results show that the plural partial areas including an image pattern that was useful for the matching was extracted by the proposed method and processing time for image matching was reduced to 50%. The proposed method has a higher reliability in comparison with the conventional methods.
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High-speed image matching using partial template consisting of multiple rectangular areas extracted by genetic algorithm
Electronics and Communications in Japan, 2011Co-Authors: Keita Okada, Fumihiko SaitohAbstract:In Normalized Correlation matching, a template image is set by manual operation before the matching process. Namely, the contents and the size of a template image are determined by the human sense. This paper proposes a method to perform a high-speed Normalized Correlation matching by extracting plural partial areas automatically that is effective in the image matching. These extracted plural partial areas become the new template image. The proposed method extracts plural partial areas suitable for matching by genetic algorithm. The experimental results show that the plural partial areas including an image pattern that was useful for the matching was extracted by the proposed method and processing time for image matching was reduced to 50%. The proposed method has a higher reliability in comparison with the conventional methods. © 2010 The Institute of Electrical Engineers of Japan.
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Moving object detection based on Correlation rate subtraction using local region template matching
Eighth International Conference on Quality Control by Artificial Vision, 2007Co-Authors: Kunihiro Goto, Fumihiko Saitoh, Kazuhiko Yamamoto, Kunihito KatoAbstract:This paper proposes a method to detect moving objects by the background subtraction using the Normalized Correlation matching. The Normalized Correlation matching is known as one of general-purposed template matching methods. And the method is robust against change of brightness. Therefore, it is expected that the stable detection of moving objects will be performed by using the Normalized Correlation matching against changing brightness of background. The proposed method regards the background image as the template image and evaluates Correlation rates between the background image and the scene image in order to extract moving objects. We also adopt the integration technique of the Correlation rate to realize more stable detection.
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image template matching by selecting block areas based on Normalized Correlation rates
Journal of The Japan Society for Precision Engineering, 2001Co-Authors: Fumihiko SaitohAbstract:This paper proposed a method for image template matching that is robust to the occlusion of a target image area. A template image is separated into local block areas and the Normalized Correlation rates are calculated in all block areas. Only partial block areas that may be useful for matching are selected according to the thresholds for the Normalized Correlation rates in all block areas that are set through the template matching using the reference images. The experimental results show that the proposed method was robust to the occlusion of the target image in comparison with the conventional methods because it can search the target image area successfully even if the 90% of the target image area is occluded.
Shuoling Peng - One of the best experts on this subject based on the ideXlab platform.
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a novel quantization watermarking scheme by modulating the Normalized Correlation
International Conference on Acoustics Speech and Signal Processing, 2012Co-Authors: Shuoling PengAbstract:This paper presents a novel quantization based watermarking scheme. Watermark embedding is performed through modulating the Normalized Correlation between the host vector and a random vector with dither modulation. The watermarked signal is derived to provide the modulated Normalized Correlation in the sense of minimizing the embedding distortion. The proposed scheme is theoretically invariant to valumetric scaling and can resist stronger noise than the well-known spread transform dither modulation. Numerical simulations on real images show that it achieves the good imperceptibility and strong robustness against a wide range of attacks.
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ICASSP - A novel quantization watermarking scheme by modulating the Normalized Correlation
2012 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2012Co-Authors: Shuoling PengAbstract:This paper presents a novel quantization based watermarking scheme. Watermark embedding is performed through modulating the Normalized Correlation between the host vector and a random vector with dither modulation. The watermarked signal is derived to provide the modulated Normalized Correlation in the sense of minimizing the embedding distortion. The proposed scheme is theoretically invariant to valumetric scaling and can resist stronger noise than the well-known spread transform dither modulation. Numerical simulations on real images show that it achieves the good imperceptibility and strong robustness against a wide range of attacks.
Ravi R. Mazumdar - One of the best experts on this subject based on the ideXlab platform.
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On the Correlation Structure of the Wavelet Coefficients of Fractional Brownian Motion
IEEE Transactions on Information Theory, 1994Co-Authors: Robert W. Dijkerman, Ravi R. MazumdarAbstract:In this correspondence, we show that the interdependence of the discrete wavelet coefficients of fractional Brownian motion, defined by the Normalized Correlation, decays exponentially fast across scales and hyperbolically fast along time. © 1994 IEEE
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On the Correlation structure of the wavelet coefficients of fractional Brownian motion
IEEE Transactions on Information Theory, 1994Co-Authors: Robert W. Dijkerman, Ravi R. MazumdarAbstract:Shows that the interdependence of the discrete wavelet coefficients of fractional Brownian motion, defined by Normalized Correlation, decays exponentially fast across scales and hyperbolically fast along time.
Jason S Chang - One of the best experts on this subject based on the ideXlab platform.
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acquiring translation equivalences of multiword expressions by Normalized Correlation frequencies
Empirical Methods in Natural Language Processing, 2009Co-Authors: Kehjiann Chen, Jason S ChangAbstract:In this paper, we present an algorithm for extracting translations of any given multiword expression from parallel corpora. Given a multiword expression to be translated, the method involves extracting a short list of target candidate words from parallel corpora based on scores of Normalized frequency, generating possible translations and filtering out common subsequences, and selecting the top-n possible translations using the Dice coefficient. Experiments show that our approach outperforms the word alignment-based and other naive association-based methods. We also demonstrate that adopting the extracted translations can significantly improve the performance of the Moses machine translation system.
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EMNLP - Acquiring Translation Equivalences of Multiword Expressions by Normalized Correlation Frequencies
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 2 - EMNLP '09, 2009Co-Authors: Kehjiann Chen, Jason S ChangAbstract:In this paper, we present an algorithm for extracting translations of any given multiword expression from parallel corpora. Given a multiword expression to be translated, the method involves extracting a short list of target candidate words from parallel corpora based on scores of Normalized frequency, generating possible translations and filtering out common subsequences, and selecting the top-n possible translations using the Dice coefficient. Experiments show that our approach outperforms the word alignment-based and other naive association-based methods. We also demonstrate that adopting the extracted translations can significantly improve the performance of the Moses machine translation system.
George L Gerstein - One of the best experts on this subject based on the ideXlab platform.
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multiunit Normalized cross Correlation differs from the average single unit Normalized Correlation
Neural Computation, 1997Co-Authors: Purvis Bedenbaugh, George L GersteinAbstract:As the technology for simultaneously recording from many brain locations becomes more available, more and more laboratories are measuring the cross-Correlation between single-neuron spike trains, and between composite spike trains derived from several undiscriminated cells recorded on a single electrode (multiunit clusters). The relationship between single-unit Correlations and multiunit cluster Correlations has not yet been fully explored. We calculated the Normalized cross-Correlation (NCC) between single unit spike trains and between small clusters of units recorded in the rat somatosensory cortex. The NCC between small clusters of units was larger than the NCC between single units. To understand this result, we investigated the scaling of the NCC with the number of units in a cluster. Multiunit cross-Correlation can be a more sensitive detector of neuronal relationship than single-unit cross-Correlation. However, changes in multiunit cross-Correlation are difficult to interpret uniquely because they d...
