2009 16th International Conference on Systems, Signals and Image Processing, 2009
A real time image based system is presented that is able to measure eye movement related quantiti... more A real time image based system is presented that is able to measure eye movement related quantities at high frame rate. The system's hardware component allows for high frame rate image acquisition under near infrared constant lighting conditions, whereas the software component is capable of performing real time image processing to determine the values of the required eye-related parameters. The measured quantities include blink parameters, eye-lid parameters and pupil diameter. The robustness of the proposed system is tested for different types of iris color, as well as under normal lighting conditions and near Infra-red light. The results are validated by off-line observer based inspection of the video sequences.
Signal processing is a fundamental component of almost any sensor-enabled system, with a wide ran... more Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.
Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference
Skin cancer is one of the most diagnosed cancers according to the World Health Organization and o... more Skin cancer is one of the most diagnosed cancers according to the World Health Organization and one of the most malignant. Unfortunately, still the available annotated data are in most cases not enough to successfully train deep learning algorithms that would allow highly accurate predictions. In this paper, we propose the utilization of transfer learning to fine-tune the parameters at the very last layers of a pre-trained a deep learning neural network. We expect that a limited number of skin lesion images is enough to affect significantly the later data-specific layers. Furthermore, we propose a pre-process step for skin lesion images that segments and crops the lesion, whereas smooths the effect of image masking, thus enhancing the network’s classification capabilities. The reported results are very promising, since the overall accuracy, as well as the accuracy of individual class classification improved in 7 out of the 8 classes, suggesting future developments in medical diagnosis through pre-trained deep learning models and specialized image prefiltering.
In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (... more In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (CNNs). More specifically, we investigate the value of augmenting CNN inputs with the response of mid-level computer vision filters, using the traditional inputting of simple RGB pixel values as baseline. The proposed methodology is applied on two pattern recognition problems with clinical significance: the binary classification of skin lesions in dermoscopy images into “malignant” and “non-malignant” (nevus skin lesions) cases and the four-class, superpixel classification into differential structures that appear in skin lesions. The transfer learning technique is also utilized to compensate for the limited size of the available training image datasets. Results show that filter-based input augmentation using the response of mid-level computer vision filters significantly improves the classification accuracy achieved by the CNN architectures and simplifies the weights of the receptive fields.
This work proposes a fully automated approach for vision-based quality control of manufactured me... more This work proposes a fully automated approach for vision-based quality control of manufactured metal rods. The proposed approach is able to detect the main axis of the rod and calculate its curvature, versus specifications. The proposed algorithm utilizes video acquired in real time by a single mono-ocular USB camera. A signal processing module identifies in real time the video frame that images the rod at the appropriate position on the conveyor. Initialization of the algorithm can take place either manually, or by utilizing the calibration of the camera. Concurrently, the image processing module estimates the curvature of the rod using its medial axis, to classify the rod as normal or defect. Initial results show that the proposed algorithm can operate in real time with very high accuracy under controlled illumination conditions and backgrounds. This methodology is capable of processing video at 30 frames per second, using a general purpose laptop.
2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016
Reconstructing shape from silhouettes is an interesting topic in computer vision. In the case of ... more Reconstructing shape from silhouettes is an interesting topic in computer vision. In the case of projective (pinhole) cameras, this task has been solved with several variations. The increasing use of omnidirectional cameras, due to their apparent advantage of covering 180 degrees field of view, necessitates the application of shape from silhouette in cases of mixed type cameras, a subject not very well studied. In this work we describe an experimental setup of three very low cost projective IP cameras, combined with a ceiling-based fisheye camera (a special type of omni-directional camera). Results are presented in reconstructing synthetic 3D human models, as well as real human subjects. Results show that including the fisheye camera enhances the accuracy of the reconstruction.
2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016
This work proposes a fully automated approach for vision-based quality control of manufactured me... more This work proposes a fully automated approach for vision-based quality control of manufactured metal rods. The proposed approach is able to detect the features of the rod (holes) and calculate the curvature of the object versus specifications. The proposed algorithm utilizes a single mono-ocular image. Initial results show that the proposed algorithm can operate under various camera geometric setups, as well as illumination conditions and backgrounds. This methodology is capable of processing an image in less than 0.2 second, using a general purpose laptop. Thus, we provide the capability for real time processing of manufactured parts on a moving conveyor.
In this paper, a novel and efficient implementation of the Marching Cubes (MC) algorithm is prese... more In this paper, a novel and efficient implementation of the Marching Cubes (MC) algorithm is presented for the reconstruction of anatomical structures from real three-dimensional medical data. The proposed approach is based on a generic rule, able to triangulate all 15 standard cube configurations used in the classical MC algorithm as well as additional cases presented in the literature. The
In this paper, an automatic method for determining pairs of corresponding points between medical ... more In this paper, an automatic method for determining pairs of corresponding points between medical images is proposed. The method is based on the implementation of an artificial immune system (AIS). AIS is a relatively novel, population based category of algorithms, inspired by theoretical immunologic models. When used as function optimizers, AIS have the attractive property of locating the global optimum of a function as well as a large number of strong local optimum points. In this work, AIS has been applied both for the extraction of an optimal set of candidate points on the reference image and the definition of their corresponding ones on the second image. The performance of the proposed AIS algorithm is evaluated against the widely used Iterative Closest Point (ICP) algorithm in terms of the accuracy of the obtained correspondences and in terms of the accuracy of the point-based registration by the two correspondence algorithms and the Mutual Information criterion, as an intensity-based registration method. Qualitative and quantitative results involving 92 X-ray dental and 10 retinal image pairs subject to known and unknown transformations are presented. The results indicate a superior performance of the proposed AIS algorithm with respect to the ICP algorithm and the Mutual Information, in terms of both correct correspondence and registration accuracy.
2009 16th International Conference on Systems, Signals and Image Processing, 2009
A real time image based system is presented that is able to measure eye movement related quantiti... more A real time image based system is presented that is able to measure eye movement related quantities at high frame rate. The system's hardware component allows for high frame rate image acquisition under near infrared constant lighting conditions, whereas the software component is capable of performing real time image processing to determine the values of the required eye-related parameters. The measured quantities include blink parameters, eye-lid parameters and pupil diameter. The robustness of the proposed system is tested for different types of iris color, as well as under normal lighting conditions and near Infra-red light. The results are validated by off-line observer based inspection of the video sequences.
Signal processing is a fundamental component of almost any sensor-enabled system, with a wide ran... more Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.
Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference
Skin cancer is one of the most diagnosed cancers according to the World Health Organization and o... more Skin cancer is one of the most diagnosed cancers according to the World Health Organization and one of the most malignant. Unfortunately, still the available annotated data are in most cases not enough to successfully train deep learning algorithms that would allow highly accurate predictions. In this paper, we propose the utilization of transfer learning to fine-tune the parameters at the very last layers of a pre-trained a deep learning neural network. We expect that a limited number of skin lesion images is enough to affect significantly the later data-specific layers. Furthermore, we propose a pre-process step for skin lesion images that segments and crops the lesion, whereas smooths the effect of image masking, thus enhancing the network’s classification capabilities. The reported results are very promising, since the overall accuracy, as well as the accuracy of individual class classification improved in 7 out of the 8 classes, suggesting future developments in medical diagnosis through pre-trained deep learning models and specialized image prefiltering.
In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (... more In this work, we focus in the analysis of dermoscopy images using convolutional neural networks (CNNs). More specifically, we investigate the value of augmenting CNN inputs with the response of mid-level computer vision filters, using the traditional inputting of simple RGB pixel values as baseline. The proposed methodology is applied on two pattern recognition problems with clinical significance: the binary classification of skin lesions in dermoscopy images into “malignant” and “non-malignant” (nevus skin lesions) cases and the four-class, superpixel classification into differential structures that appear in skin lesions. The transfer learning technique is also utilized to compensate for the limited size of the available training image datasets. Results show that filter-based input augmentation using the response of mid-level computer vision filters significantly improves the classification accuracy achieved by the CNN architectures and simplifies the weights of the receptive fields.
This work proposes a fully automated approach for vision-based quality control of manufactured me... more This work proposes a fully automated approach for vision-based quality control of manufactured metal rods. The proposed approach is able to detect the main axis of the rod and calculate its curvature, versus specifications. The proposed algorithm utilizes video acquired in real time by a single mono-ocular USB camera. A signal processing module identifies in real time the video frame that images the rod at the appropriate position on the conveyor. Initialization of the algorithm can take place either manually, or by utilizing the calibration of the camera. Concurrently, the image processing module estimates the curvature of the rod using its medial axis, to classify the rod as normal or defect. Initial results show that the proposed algorithm can operate in real time with very high accuracy under controlled illumination conditions and backgrounds. This methodology is capable of processing video at 30 frames per second, using a general purpose laptop.
2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016
Reconstructing shape from silhouettes is an interesting topic in computer vision. In the case of ... more Reconstructing shape from silhouettes is an interesting topic in computer vision. In the case of projective (pinhole) cameras, this task has been solved with several variations. The increasing use of omnidirectional cameras, due to their apparent advantage of covering 180 degrees field of view, necessitates the application of shape from silhouette in cases of mixed type cameras, a subject not very well studied. In this work we describe an experimental setup of three very low cost projective IP cameras, combined with a ceiling-based fisheye camera (a special type of omni-directional camera). Results are presented in reconstructing synthetic 3D human models, as well as real human subjects. Results show that including the fisheye camera enhances the accuracy of the reconstruction.
2016 IEEE International Conference on Imaging Systems and Techniques (IST), 2016
This work proposes a fully automated approach for vision-based quality control of manufactured me... more This work proposes a fully automated approach for vision-based quality control of manufactured metal rods. The proposed approach is able to detect the features of the rod (holes) and calculate the curvature of the object versus specifications. The proposed algorithm utilizes a single mono-ocular image. Initial results show that the proposed algorithm can operate under various camera geometric setups, as well as illumination conditions and backgrounds. This methodology is capable of processing an image in less than 0.2 second, using a general purpose laptop. Thus, we provide the capability for real time processing of manufactured parts on a moving conveyor.
In this paper, a novel and efficient implementation of the Marching Cubes (MC) algorithm is prese... more In this paper, a novel and efficient implementation of the Marching Cubes (MC) algorithm is presented for the reconstruction of anatomical structures from real three-dimensional medical data. The proposed approach is based on a generic rule, able to triangulate all 15 standard cube configurations used in the classical MC algorithm as well as additional cases presented in the literature. The
In this paper, an automatic method for determining pairs of corresponding points between medical ... more In this paper, an automatic method for determining pairs of corresponding points between medical images is proposed. The method is based on the implementation of an artificial immune system (AIS). AIS is a relatively novel, population based category of algorithms, inspired by theoretical immunologic models. When used as function optimizers, AIS have the attractive property of locating the global optimum of a function as well as a large number of strong local optimum points. In this work, AIS has been applied both for the extraction of an optimal set of candidate points on the reference image and the definition of their corresponding ones on the second image. The performance of the proposed AIS algorithm is evaluated against the widely used Iterative Closest Point (ICP) algorithm in terms of the accuracy of the obtained correspondences and in terms of the accuracy of the point-based registration by the two correspondence algorithms and the Mutual Information criterion, as an intensity-based registration method. Qualitative and quantitative results involving 92 X-ray dental and 10 retinal image pairs subject to known and unknown transformations are presented. The results indicate a superior performance of the proposed AIS algorithm with respect to the ICP algorithm and the Mutual Information, in terms of both correct correspondence and registration accuracy.
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