Papers by Dimitrios Makris
arXiv (Cornell University), Feb 13, 2023
Image fusion methods have gained a lot of attraction over the past few years in the field of sens... more Image fusion methods have gained a lot of attraction over the past few years in the field of sensor fusion. An efficient image fusion approach can obtain complementary information from various multi-modality images. In addition, the fused image is more robust to imperfect conditions such as mis-registration and noise. The aim of this paper is to explore the performance of existing deep learning-based and traditional image fusion techniques for our real marine images. The performance of these techniques is evaluated with six common quality metrics. Image data was collected using a sensor system onboard a vessel in the Finnish archipelago. This system is used for developing autonomous vessels, and records data in a range of operation and climatic conditions. To the best of our knowledge, there is not a comparative study of RGB and infrared image fusion algorithms evaluated in a marine environment. Experimental results indicate that deep learning-based fusion methods can significantly improve the image fusion performance considering both the visual quality and objective assessment comparison against with other methods.
arXiv (Cornell University), May 5, 2023
Iet Computer Vision, Jan 3, 2018
arXiv (Cornell University), Mar 20, 2023
2018 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), 2018
The daltonization process refers to the color adaptation of images in order to improve the percep... more The daltonization process refers to the color adaptation of images in order to improve the perception of color-blind viewers. This paper proposes a modified clustering approach, which is applied to color adaptation of digitized art paintings and concerns a specific color vision deficiency called protanopia. To accomplish this task, the objective function of the fuzzy c-means is reformulated as to include only the cluster centers, and then it is minimized by the differential evolution. By using a standard technique, the original image is transformed to simulate the effect of the protanopia deficiency. Then, the above-mentioned clustering approach is separately applied to the original and the protanopia simulated images. By comparing the color clusters between these two cases, the colors in the original image are classified into two classes: (a) colors that must be corrected so that a protanope can easily distinguish them, and (b) colors that must remain intact. To this end, the colors belonging to the former class are adapted subject to the constraint that they must not be similar to the colors belonging to the latter class. Finally, the effectiveness of the proposed methodology is demonstrated through a number of experiments on color art paintings.
11th International Conference of Pattern Recognition Systems (ICPRS 2021), 2021
Sensors (Basel, Switzerland), Jan 24, 2018
In this paper, a novel approach to detect incipient slip based on the contact area between a tran... more In this paper, a novel approach to detect incipient slip based on the contact area between a transparent silicone medium and different objects using a neuromorphic event-based vision sensor (DAVIS) is proposed. Event-based algorithms are developed to detect incipient slip, slip, stress distribution and object vibration. Thirty-seven experiments were performed on five objects with different sizes, shapes, materials and weights to compare precision and response time of the proposed approach. The proposed approach is validated by using a high speed constitutional camera (1000 FPS). The results indicate that the sensor can detect incipient slippage with an average of 44.1 ms latency in unstructured environment for various objects. It is worth mentioning that the experiments were conducted in an uncontrolled experimental environment, therefore adding high noise levels that affected results significantly. However, eleven of the experiments had a detection latency below 10 ms which shows t...
Pattern Recognition Letters, Sep 1, 2010
Springer eBooks, Dec 22, 2005
An important capability of an ambient intelligent environment is the capacity to detect, locate a... more An important capability of an ambient intelligent environment is the capacity to detect, locate and identify objects of interest. In many cases interesting can move, and in order to provide meaningful interaction, capturing and tracking the motion creates a perceptively-enabled interface, capable of understanding and reacting to a wide range of actions and activities. CCTV systems fulfill an increasingly important role in the modern world, providing live video access to remote environments. Whilst the role of CCTV has been primarily focused on ...
Lecture Notes in Computer Science, 2008
Ultrasound in Medicine and Biology, Jun 1, 2019
Pattern Analysis and Applications, Dec 1, 2004
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Papers by Dimitrios Makris