Pub Date : 2019-05-06DOI: 10.4236/JSIP.2019.102004
Muhammad Irfan Aziz, T. Owens, Uzair Khaleeq-uz-Zaman, Muhammad B. Akbar
Localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles is a current need. Many techniques have been discussed in the literature with respect to location-based services and techniques used for the positioning of devices. Time difference of arrival (TDOA), time of arrival (TOA) and received signal strength (RSS) have been widely used for the positioning but narrow band signals such as Bluetooth cannot efficiently utilize TDOA or TOA. Received signal strength indicator (RSSI) to measure RSS, has been found to be more reliable. RSSI measurement estimations depend heavily on the environmental interference. RSSI measurement estimations of Bluetooth systems can be improved either by improving the existing methodologies used to implement them or by using fusion techniques that employ Kalman filters to combine more than one RSSI method to improve the results significantly. This paper focuses on improving the existing methodology of measuring RSSI by proposing a new method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the new method, class 2 Bluetooth devices (Blue Giga WT-12) were used with an evaluation board. The software required was developed in National Instruments LabView. The PCB was designed and manufactured as well. Experiments were then conducted, and surface plots of Bluetooth modules were obtained to show the signal interference and other environmental effects. Lastly, the results were discussed, and relevant conclusions were drawn.
{"title":"RSSI Based Localization of Bluetooth Devices for Visually Impaired","authors":"Muhammad Irfan Aziz, T. Owens, Uzair Khaleeq-uz-Zaman, Muhammad B. Akbar","doi":"10.4236/JSIP.2019.102004","DOIUrl":"https://doi.org/10.4236/JSIP.2019.102004","url":null,"abstract":"Localization for visually impaired people in dynamically changing environments with unexpected hazards and obstacles is a current need. Many techniques have been discussed in the literature with respect to location-based services and techniques used for the positioning of devices. Time difference of arrival (TDOA), time of arrival (TOA) and received signal strength (RSS) have been widely used for the positioning but narrow band signals such as Bluetooth cannot efficiently utilize TDOA or TOA. Received signal strength indicator (RSSI) to measure RSS, has been found to be more reliable. RSSI measurement estimations depend heavily on the environmental interference. RSSI measurement estimations of Bluetooth systems can be improved either by improving the existing methodologies used to implement them or by using fusion techniques that employ Kalman filters to combine more than one RSSI method to improve the results significantly. This paper focuses on improving the existing methodology of measuring RSSI by proposing a new method using trilateration for localization of Bluetooth devices for visually impaired people. To validate the new method, class 2 Bluetooth devices (Blue Giga WT-12) were used with an evaluation board. The software required was developed in National Instruments LabView. The PCB was designed and manufactured as well. Experiments were then conducted, and surface plots of Bluetooth modules were obtained to show the signal interference and other environmental effects. Lastly, the results were discussed, and relevant conclusions were drawn.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78420760","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 : 2019-01-01DOI: 10.4236/JSIP.2019.101001
Amber Khan, Mariam Nida Usmani, Nashrah Rahman, D. Prasad
In this paper, we propose a novel method to enhance the OCR (Optical Character Recognition) readability of public signboards captured by smart-phone cameras—both outdoors and indoors, and subject to various lighting conditions. A distinct feature of our technique is the detection of these signs in the HSV (Hue, Saturation and Value) color space, done in order to filter out the signboard from the background, and correctly interpret the textual details of each signboard. This is then binarized using a thresholding technique that is optimized for text printed on contrasting backgrounds, and passed through the Tesseract engine to detect individual characters. We test out our technique on a dataset of over 200 images taken in and around the campus of our college, and are successful in attaining better OCR results in comparison to traditional methods. Further, we suggest the utilization of a method to automatically assign ROIs (Regions Of Interest) to detected signboards, for better recognition of textual information.
{"title":"Pre-Processing Images of Public Signage for OCR Conversion","authors":"Amber Khan, Mariam Nida Usmani, Nashrah Rahman, D. Prasad","doi":"10.4236/JSIP.2019.101001","DOIUrl":"https://doi.org/10.4236/JSIP.2019.101001","url":null,"abstract":"In this paper, we propose a novel method to enhance the OCR (Optical Character Recognition) readability of public signboards captured by smart-phone cameras—both outdoors and indoors, and subject to various lighting conditions. A distinct feature of our technique is the detection of these signs in the HSV (Hue, Saturation and Value) color space, done in order to filter out the signboard from the background, and correctly interpret the textual details of each signboard. This is then binarized using a thresholding technique that is optimized for text printed on contrasting backgrounds, and passed through the Tesseract engine to detect individual characters. We test out our technique on a dataset of over 200 images taken in and around the campus of our college, and are successful in attaining better OCR results in comparison to traditional methods. Further, we suggest the utilization of a method to automatically assign ROIs (Regions Of Interest) to detected signboards, for better recognition of textual information.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87060494","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 : 2019-01-01DOI: 10.4236/JSIP.2019.101002
Min-Cheng Pan
A number of conventional interpolation techniques have been proposed. However, it seems that there do not exist good criteria for the design of optimal linear interpolators. Also, such an interpolator can hardly provide a satisfactory solution for interpolating noisy images. In this paper, the novelty of this research is that a universal approach is proposed to design an image interpolator with any one image smoothing filter, thereby not only interpolating a down-sampled image but also preserving the characteristics of the performing filtering.
{"title":"A Universal Approach to Designing an Image Interpolator with an Image Smoothing Filter","authors":"Min-Cheng Pan","doi":"10.4236/JSIP.2019.101002","DOIUrl":"https://doi.org/10.4236/JSIP.2019.101002","url":null,"abstract":"A number of conventional interpolation techniques have been proposed. However, it seems that there do not exist good criteria for the design of optimal linear interpolators. Also, such an interpolator can hardly provide a satisfactory solution for interpolating noisy images. In this paper, the novelty of this research is that a universal approach is proposed to design an image interpolator with any one image smoothing filter, thereby not only interpolating a down-sampled image but also preserving the characteristics of the performing filtering.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81822448","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 : 2019-01-01DOI: 10.4236/JSIP.2019.101003
Amin Ebrahimi Bardar, B. Oskooi, A. Goudarzi
Ground Penetration Radar is a controlled source geophysical method which uses high frequency electromagnetic waves to study shallow layers. Resolution of this method depends on difference of electrical properties between target and surrounding electrical medium, target geometry and used bandwidth. The wavelet transform is used extensively in signal analysis and noise attenuation. In addition, wavelet domain allows local precise descriptions of signal behavior. The Fourier coefficient represents a component for all time and therefore local events must be described by the phase characteristic which can be abolished or strengthened over a large period of time. Finally basis of Auto Regression (AR) is the fitting of an appropriate model on data, which in practice results in more information from data process. Estimation of the parameters of the regression model (AR) is very important. In order to obtain a higher-resolution spectral estimation than other models, recursive operator is a suitable tool. Generally, it is much easier to work with an Auto Regression model. Results shows that the TQWT in soft thresholding mode can attenuate random noise far better than TQWT in hard thresholding mode and Autoregressive-FX method.
{"title":"Comparison of GPR Random Noise Attenuation Using Autoregressive-FX Method and Tunable Quality Factor Wavelet Transform TQWT with Soft and Hard Thresholding","authors":"Amin Ebrahimi Bardar, B. Oskooi, A. Goudarzi","doi":"10.4236/JSIP.2019.101003","DOIUrl":"https://doi.org/10.4236/JSIP.2019.101003","url":null,"abstract":"Ground Penetration Radar is a controlled source geophysical method which uses high frequency electromagnetic waves to study shallow layers. Resolution of this method depends on difference of electrical properties between target and surrounding electrical medium, target geometry and used bandwidth. The wavelet transform is used extensively in signal analysis and noise attenuation. In addition, wavelet domain allows local precise descriptions of signal behavior. The Fourier coefficient represents a component for all time and therefore local events must be described by the phase characteristic which can be abolished or strengthened over a large period of time. Finally basis of Auto Regression (AR) is the fitting of an appropriate model on data, which in practice results in more information from data process. Estimation of the parameters of the regression model (AR) is very important. In order to obtain a higher-resolution spectral estimation than other models, recursive operator is a suitable tool. Generally, it is much easier to work with an Auto Regression model. Results shows that the TQWT in soft thresholding mode can attenuate random noise far better than TQWT in hard thresholding mode and Autoregressive-FX method.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"34 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87113035","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}
In this paper, we propose a low-cost posture recognition scheme using a single webcam for the signaling hand with nature sways and possible oc-clusions. It goes for developing the untouchable low-complexity utility based on friendly hand-posture signaling. The scheme integrates the dominant temporal-difference detection, skin color detection and morphological filtering for efficient cooperation in constructing the hand profile molds. Those molds provide representative hand profiles for more stable posture recognition than accurate hand shapes with in effect trivial details. The resultant bounding box of tracking the signaling molds can be treated as a regular-type object-matched ROI to facilitate the stable extraction of robust HOG features. With such commonly applied features on hand, the prototype SVM is adequately capable of obtaining fast and stable hand postures recognition under natural hand movement and non-hand object occlusion. Experimental results demonstrate that our scheme can achieve hand-posture recognition with enough accuracy under background clutters that the targeted hand can be allowed with medium movement and palm-grasped object. Hence, the proposed method can be easily embedded in the mobile phone as application software.
{"title":"Low-Cost Posture Recognition of Moving Hands by Profile-Mold Construction in Cluttered Background and Occlusion","authors":"Din-Yuen Chan, Guanyu Lin, Xi-Wen Wu","doi":"10.4236/JSIP.2018.94016","DOIUrl":"https://doi.org/10.4236/JSIP.2018.94016","url":null,"abstract":"In this paper, we propose a low-cost posture recognition scheme using a single webcam for the signaling hand with nature sways and possible oc-clusions. It goes for developing the untouchable low-complexity utility based on friendly hand-posture signaling. The scheme integrates the dominant temporal-difference detection, skin color detection and morphological filtering for efficient cooperation in constructing the hand profile molds. Those molds provide representative hand profiles for more stable posture recognition than accurate hand shapes with in effect trivial details. The resultant bounding box of tracking the signaling molds can be treated as a regular-type object-matched ROI to facilitate the stable extraction of robust HOG features. With such commonly applied features on hand, the prototype SVM is adequately capable of obtaining fast and stable hand postures recognition under natural hand movement and non-hand object occlusion. Experimental results demonstrate that our scheme can achieve hand-posture recognition with enough accuracy under background clutters that the targeted hand can be allowed with medium movement and palm-grasped object. Hence, the proposed method can be easily embedded in the mobile phone as application software.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"31 1","pages":"258-265"},"PeriodicalIF":0.0,"publicationDate":"2018-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84935670","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}
J. Fourniols, N. Nasreddine, C. Escriba, P. Acco, J. Roux, G. S. Romero
Automatic speech recognition, often incorrectly called voice recognition, is a computer based software technique that analyzes audio signals captured by a microphone and translates them into machine interpreted text. Speech processing is based on techniques that need local CPU or cloud computing with an Internet link. An activation word starts the uplink; “OK google”, “Alexa”, … and voice analysis is not usually suitable for autonomous limited CPU system (16 bits microcontroller) with low energy. To achieve this realization, this paper presents specific techniques and details an efficiency voice command method compatible with an embedded IOT low-power device.
{"title":"An Overview of Basics Speech Recognition and Autonomous Approach for Smart Home IOT Low Power Devices","authors":"J. Fourniols, N. Nasreddine, C. Escriba, P. Acco, J. Roux, G. S. Romero","doi":"10.4236/JSIP.2018.94015","DOIUrl":"https://doi.org/10.4236/JSIP.2018.94015","url":null,"abstract":"Automatic speech recognition, often incorrectly called voice recognition, is a computer based software technique that analyzes audio signals captured by a microphone and translates them into machine interpreted text. Speech processing is based on techniques that need local CPU or cloud computing with an Internet link. An activation word starts the uplink; “OK google”, “Alexa”, … and voice analysis is not usually suitable for autonomous limited CPU system (16 bits microcontroller) with low energy. To achieve this realization, this paper presents specific techniques and details an efficiency voice command method compatible with an embedded IOT low-power device.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"51 3","pages":"239-257"},"PeriodicalIF":0.0,"publicationDate":"2018-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72470724","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 : 2018-10-12DOI: 10.1007/978-3-030-03766-6_86
Qing Wu, Bo-yan Zang, Yu Zhang, Zongxian Qi
{"title":"Wavelet Kernel Twin Support Vector Machine","authors":"Qing Wu, Bo-yan Zang, Yu Zhang, Zongxian Qi","doi":"10.1007/978-3-030-03766-6_86","DOIUrl":"https://doi.org/10.1007/978-3-030-03766-6_86","url":null,"abstract":"","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"8 1","pages":"93-101"},"PeriodicalIF":0.0,"publicationDate":"2018-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79882679","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}
Short Retraction Notice The authors claim that this paper needs modifications. This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) The full retraction notice in PDF is preceding the original paper, which is marked "RETRACTED".
{"title":"RETRACTED: Realization of Virtual Human Face Based on Deep Convolutional Generative Adversarial Networks","authors":"Zijiang Zhu, Xiaoguang Deng, Junshan Li, E. Wei","doi":"10.4236/JSIP.2018.93013","DOIUrl":"https://doi.org/10.4236/JSIP.2018.93013","url":null,"abstract":"Short Retraction Notice \u0000 \u0000 \u0000 The authors claim that this paper needs modifications. \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 This article has been retracted to straighten the academic record. In making this decision the Editorial Board follows COPE's Retraction Guidelines. The aim is to promote the circulation of scientific research by offering an ideal research publication platform with due consideration of internationally accepted standards on publication ethics. The Editorial Board would like to extend its sincere apologies for any inconvenience this retraction may have caused. \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 Editor guiding this retraction: Prof. Baozong Yuan(EiC of JSIP) \u0000 \u0000 \u0000 \u0000 \u0000 \u0000 The full retraction notice in PDF is preceding the original paper, which is marked \"RETRACTED\".","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"4 1","pages":"217-228"},"PeriodicalIF":0.0,"publicationDate":"2018-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90928096","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}
The paper discusses the quantitative definition of the s/n (signal to noise ratio) by means of new computational parameters derived (and computed) by the Fourier analysis. The theme is of great relevance when the geomagnetic observed field has high transient noise and high energy content (i.e.geomagnetic signal interfered by human activity magnetic band) and when the signal analysis action is oriented to the detection of magnetic sources characterized by quasi-punctiform size, low energy level and kinetic mechanical status (i.e.uw armed terrorist). The paper shows the results obtained introducing two new informative spectral parameters: the informative capability “C” and the enhanced informative capability “eC”. These parameters are depending on the comparison of the energy of the target signal with total field energy and they are characteristics of each elementary signal. C classifies the energy of the spectrum in two metrological bands: elementary signal informative energy EI (band or single signal) and passive energy EP. This metrological classification of the energy overtakes the concept of noise: each signal is part of the noise band when it is not under observation and becomes out of the band when it is under observation (numerical observation→computation). C (and eC) allows to compute the value of the “visibility” of the informative signals in a high energy geomagnetic field (or spectrum). C is a fundamental parameter for the evaluation of the effectiveness of singularity magnetic metrology in the passive detection of small magnetic sources in high noised magnetic field.
{"title":"The Fourier Notation of the Geomagnetic Signals Informative Parameters","authors":"O. Faggioni","doi":"10.4236/JSIP.2018.93009","DOIUrl":"https://doi.org/10.4236/JSIP.2018.93009","url":null,"abstract":"The paper discusses the quantitative definition of the s/n (signal to noise ratio) by means of new computational parameters derived (and computed) by the Fourier analysis. The theme is of great relevance when the geomagnetic observed field has high transient noise and high energy content (i.e.geomagnetic signal interfered by human activity magnetic band) and when the signal analysis action is oriented to the detection of magnetic sources characterized by quasi-punctiform size, low energy level and kinetic mechanical status (i.e.uw armed terrorist). The paper shows the results obtained introducing two new informative spectral parameters: the informative capability “C” and the enhanced informative capability “eC”. These parameters are depending on the comparison of the energy of the target signal with total field energy and they are characteristics of each elementary signal. C classifies the energy of the spectrum in two metrological bands: elementary signal informative energy EI (band or single signal) and passive energy EP. This metrological classification of the energy overtakes the concept of noise: each signal is part of the noise band when it is not under observation and becomes out of the band when it is under observation (numerical observation→computation). C (and eC) allows to compute the value of the “visibility” of the informative signals in a high energy geomagnetic field (or spectrum). C is a fundamental parameter for the evaluation of the effectiveness of singularity magnetic metrology in the passive detection of small magnetic sources in high noised magnetic field.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"75 1","pages":"153-166"},"PeriodicalIF":0.0,"publicationDate":"2018-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80198426","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}
The quaternion linear canonical transform (QLCT) is defined in this paper, with proofs given for its reversibility property, its linear property, its odd-even invariant property and additivity property. Meanwhile, the quaternion convolution (QCV), quaternion correlation (QCR) and product theorem of LCT are deduced. Their physical interpretation is given as classical convolution, correlation and product theorem. Moreover, the fast algorithm of QLCT (FQLCT) is obtained, whose calculation complexity for different signals is similar to FFT. In addition, the paper presents the relationship between the convolution and correlation in LCT domains, and the convolution and correlation can be calculated via product theorem in Fourier transform domain using FFT.
{"title":"The Properties and Fast Algorithm of Quaternion Linear Canonical Transform","authors":"Yehui Zhang, Guanlei Xu","doi":"10.4236/JSIP.2018.93012","DOIUrl":"https://doi.org/10.4236/JSIP.2018.93012","url":null,"abstract":"The quaternion linear canonical transform (QLCT) is defined in this paper, with proofs given for its reversibility property, its linear property, its odd-even invariant property and additivity property. Meanwhile, the quaternion convolution (QCV), quaternion correlation (QCR) and product theorem of LCT are deduced. Their physical interpretation is given as classical convolution, correlation and product theorem. Moreover, the fast algorithm of QLCT (FQLCT) is obtained, whose calculation complexity for different signals is similar to FFT. In addition, the paper presents the relationship between the convolution and correlation in LCT domains, and the convolution and correlation can be calculated via product theorem in Fourier transform domain using FFT.","PeriodicalId":38474,"journal":{"name":"Journal of Information Hiding and Multimedia Signal Processing","volume":"111 1","pages":"202-216"},"PeriodicalIF":0.0,"publicationDate":"2018-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86741823","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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