Michele Conni | Norwegian University of Science and Technology (original) (raw)

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Thesis Chapters by Michele Conni

Research paper thumbnail of Complete mapping of magnon dispersion in antiferromagnetic layered cuprates using RIXS

Mott insulator belong to the case in which U/t 1. This theory can be exploited to represent the C... more Mott insulator belong to the case in which U/t 1. This theory can be exploited to represent the CuO 2 inplane interactions between the unpaired electron on the Cu 2+ ions (3d 9 electronic state), whose magnetic coupling is due to the superexchange eect, mediated by the oxygen anions. In fact, if the t − J Hamiltonian is expanded in series of spin operators products, it is possible to obtain a sum of Heisenberg X terms, which are characterized by the magnetic exchange parameter J. The rst

Papers by Michele Conni

Research paper thumbnail of A Versatile Multi-Camera System for 3D Acquisition and Modeling

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020

Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, d... more Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, data processing, and 3D surface generation and editing. The availability of different easy-to-use and low-cost image acquisition solutions, combined with open-source or commercial processing tools, has democratized the 3D reconstruction and digital twin generation. But high geometric and texture fidelity on small-to medium-scale objects as well as integrated commercial system for mass 3D digitization are not available. The paper presents our effort to build such a system, i.e. a market-ready multi-camera solution and a customized reconstruction process for mass 3D digitization of small to medium objects. The system is realized as a joint work between industrial and academic partners, in order to employ the latest technologies for the needs of the market. The proposed versatile image acquisition and processing system pushes to the limits the 3D digitization pipeline combining a rigid capturing system with photogrammetric reconstruction methods.

Research paper thumbnail of Measurement Uncertainty for Printed Textiles

2018 Colour and Visual Computing Symposium (CVCS), 2018

Measurement repeatability and reproducibility were analysed for four different models of colour m... more Measurement repeatability and reproducibility were analysed for four different models of colour measurement instrument on PTFE and on printed and unprinted cotton material. The influence of instrument aperture and sample characteristics on the measurements was analyzed, showing that as expected larger apertures tended to give better repeatability and smaller difference in the inter-model agreement. Measurement repeatability across the different textile samples was in the range of 0.04−0.91DeltaEabast0.04-0.91 \Delta E_{ab}^{\ast }0.04−0.91DeltaEabast, while the effect of different sample positioning was in the range of 0.25−0.88DeltaEabast0.25- 0.88 \Delta E_{ab}^{\ast }0.25−0.88DeltaEabast.

Research paper thumbnail of Dependence of texture classification accuracy on spectral information

2018 Colour and Visual Computing Symposium (CVCS), 2018

The influence of the number of spectral channels of spatial information on the accuracy of textur... more The influence of the number of spectral channels of spatial information on the accuracy of texture classification was evaluated by modelling the spectral sensitivity functions of a group of ideal imaging systems with a set of gaussian functions and then applying them to a set of hyperspectral images in order to simulate the response of each of their colour channels. Feature extraction and classification with different techniques were applied to the simulated data to assess the performance. It was shown that a significant enhancement of the accuracy was achieved, with a dependency on the approach adopted; it is therefore possible to estimate the optimal number of spectral channels for each method.

Research paper thumbnail of Visual and data stationarity of texture images

Journal of Electronic Imaging

Research paper thumbnail of Texture Stationarity Evaluation with Local Wavelet Spectrum

London Imaging Meeting

In texture analysis, stationarity is a fundamental property. There are various ways to evaluate i... more In texture analysis, stationarity is a fundamental property. There are various ways to evaluate if a texture image is stationary or not. One of the most recent and effective of these is a standard test based on non-decimated stationary wavelet transform. This method permits to evaluate how stationary is an image depending on the scale considered. We propose to use this feature to characterize an image and we discuss the implication of such approach.

Research paper thumbnail of The Effect of Camera Calibration on Multichannel Texture Classification

Journal of Imaging Science and Technology

The efficiency of a texture classification procedure depends on the color space in which it is pe... more The efficiency of a texture classification procedure depends on the color space in which it is performed. Classification in a perceptually meaningful space requires chromatic coordinates obtained from a calibrated acquisition setup. The authors assess the impact of camera calibration, within a generic color picture acquisition workflow, on the performance of a number of texture classification techniques. An image calibration pipeline is established and applied to a texture database, and the accuracy of the classification algorithms is evaluated for each step. The results show that the most significant step of the workflow is color rendering although the effect is relatively small. Hence precise scene-referred characterization of the raw data from an acquisition camera is notessential for most texture classification tasks. In addition, workingwith output-referred RGB data is likely to be adequate for the majority of classification tasks.

Research paper thumbnail of The Effect of Camera Calibration on Multichannel Texture Classification

Journal of Imaging Science and Technology

The efficiency of a texture classification procedure depends on the color space in which it is pe... more The efficiency of a texture classification procedure depends on the color space in which it is performed. Classification in a perceptually meaningful space requires chromatic coordinates obtained from a calibrated acquisition setup. The authors assess the impact of camera calibration, within a generic color picture acquisition workflow, on the performance of a number of texture classification techniques. An image calibration pipeline is established and applied to a texture database, and the accuracy of the classification algorithms is evaluated for each step. The results show that the most significant step of the workflow is color rendering although the effect is relatively small. Hence precise scene-referred characterization of the raw data from an acquisition camera is notessential for most texture classification tasks. In addition, workingwith output-referred RGB data is likely to be adequate for the majority of classification tasks.

Research paper thumbnail of Complete mapping of magnon dispersion in antiferromagnetic layered cuprates using RIXS

Mott insulator belong to the case in which U/t 1. This theory can be exploited to represent the C... more Mott insulator belong to the case in which U/t 1. This theory can be exploited to represent the CuO 2 inplane interactions between the unpaired electron on the Cu 2+ ions (3d 9 electronic state), whose magnetic coupling is due to the superexchange eect, mediated by the oxygen anions. In fact, if the t − J Hamiltonian is expanded in series of spin operators products, it is possible to obtain a sum of Heisenberg X terms, which are characterized by the magnetic exchange parameter J. The rst

Research paper thumbnail of A Versatile Multi-Camera System for 3D Acquisition and Modeling

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020

Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, d... more Image-based 3D models generation typically involves three stages, namely: 2D image acquisition, data processing, and 3D surface generation and editing. The availability of different easy-to-use and low-cost image acquisition solutions, combined with open-source or commercial processing tools, has democratized the 3D reconstruction and digital twin generation. But high geometric and texture fidelity on small-to medium-scale objects as well as integrated commercial system for mass 3D digitization are not available. The paper presents our effort to build such a system, i.e. a market-ready multi-camera solution and a customized reconstruction process for mass 3D digitization of small to medium objects. The system is realized as a joint work between industrial and academic partners, in order to employ the latest technologies for the needs of the market. The proposed versatile image acquisition and processing system pushes to the limits the 3D digitization pipeline combining a rigid capturing system with photogrammetric reconstruction methods.

Research paper thumbnail of Measurement Uncertainty for Printed Textiles

2018 Colour and Visual Computing Symposium (CVCS), 2018

Measurement repeatability and reproducibility were analysed for four different models of colour m... more Measurement repeatability and reproducibility were analysed for four different models of colour measurement instrument on PTFE and on printed and unprinted cotton material. The influence of instrument aperture and sample characteristics on the measurements was analyzed, showing that as expected larger apertures tended to give better repeatability and smaller difference in the inter-model agreement. Measurement repeatability across the different textile samples was in the range of 0.04−0.91DeltaEabast0.04-0.91 \Delta E_{ab}^{\ast }0.04−0.91DeltaEabast, while the effect of different sample positioning was in the range of 0.25−0.88DeltaEabast0.25- 0.88 \Delta E_{ab}^{\ast }0.25−0.88DeltaEabast.

Research paper thumbnail of Dependence of texture classification accuracy on spectral information

2018 Colour and Visual Computing Symposium (CVCS), 2018

The influence of the number of spectral channels of spatial information on the accuracy of textur... more The influence of the number of spectral channels of spatial information on the accuracy of texture classification was evaluated by modelling the spectral sensitivity functions of a group of ideal imaging systems with a set of gaussian functions and then applying them to a set of hyperspectral images in order to simulate the response of each of their colour channels. Feature extraction and classification with different techniques were applied to the simulated data to assess the performance. It was shown that a significant enhancement of the accuracy was achieved, with a dependency on the approach adopted; it is therefore possible to estimate the optimal number of spectral channels for each method.

Research paper thumbnail of Visual and data stationarity of texture images

Journal of Electronic Imaging

Research paper thumbnail of Texture Stationarity Evaluation with Local Wavelet Spectrum

London Imaging Meeting

In texture analysis, stationarity is a fundamental property. There are various ways to evaluate i... more In texture analysis, stationarity is a fundamental property. There are various ways to evaluate if a texture image is stationary or not. One of the most recent and effective of these is a standard test based on non-decimated stationary wavelet transform. This method permits to evaluate how stationary is an image depending on the scale considered. We propose to use this feature to characterize an image and we discuss the implication of such approach.

Research paper thumbnail of The Effect of Camera Calibration on Multichannel Texture Classification

Journal of Imaging Science and Technology

The efficiency of a texture classification procedure depends on the color space in which it is pe... more The efficiency of a texture classification procedure depends on the color space in which it is performed. Classification in a perceptually meaningful space requires chromatic coordinates obtained from a calibrated acquisition setup. The authors assess the impact of camera calibration, within a generic color picture acquisition workflow, on the performance of a number of texture classification techniques. An image calibration pipeline is established and applied to a texture database, and the accuracy of the classification algorithms is evaluated for each step. The results show that the most significant step of the workflow is color rendering although the effect is relatively small. Hence precise scene-referred characterization of the raw data from an acquisition camera is notessential for most texture classification tasks. In addition, workingwith output-referred RGB data is likely to be adequate for the majority of classification tasks.

Research paper thumbnail of The Effect of Camera Calibration on Multichannel Texture Classification

Journal of Imaging Science and Technology

The efficiency of a texture classification procedure depends on the color space in which it is pe... more The efficiency of a texture classification procedure depends on the color space in which it is performed. Classification in a perceptually meaningful space requires chromatic coordinates obtained from a calibrated acquisition setup. The authors assess the impact of camera calibration, within a generic color picture acquisition workflow, on the performance of a number of texture classification techniques. An image calibration pipeline is established and applied to a texture database, and the accuracy of the classification algorithms is evaluated for each step. The results show that the most significant step of the workflow is color rendering although the effect is relatively small. Hence precise scene-referred characterization of the raw data from an acquisition camera is notessential for most texture classification tasks. In addition, workingwith output-referred RGB data is likely to be adequate for the majority of classification tasks.