Curvature sensor based on structure of Mach-Zehnder interferometer coated with aluminum-doped zinc oxideRico-Mendez, Mario A.; Selvas, Romeo; Bazavilvazo, Sheila; Arévalo, Leonardo; García, Manuel; Chapa, Ricardo; Puente-Ramirez, Norma P.; Sierra-Hernandez, Juan M.; Gallegos-Arellano, Eloisa
doi: 10.1117/12.3027150pmid: N/A
This work presents a novel fiber optic Mach-Zehnder interferometer (MZI) sensor that can measure curvature due to its structure. This structure employs a 2-section MZI filter constructed from SMF-28 fiber using the core offset technique. The source in the 1480-1600 nm range shows intermodal energy interference between the core and the cladding and exhibits six spacing notches for sensing applications. The sensibility obtained was of 0.00018 nm/uW when curvature is applied. However, by including a thin film based on Zinc Oxide (ZnO) and another with Aluminum-doped zinc oxide (AZO) in the sensing arrangement, an increase in the sensitivity was detected with a value of 0.00015 nm/uW and 0.00016 nm/uW, respectively. This sensor can be used for applications in various fields, such as environmental monitoring, engineering, and process control.
Weight adjustment of the quantum layer in a hybrid model for skin cancer image classificationLopez, Daniel Alejandro; Montiel, Oscar; Lopez-Montiel, Miguel; Castillo, Oscar
doi: 10.1117/12.3027860pmid: N/A
Integrating quantum algorithms with machine and deep learning models has emerged as a promising method for addressing medical image classification challenges. This integration can enhance speed and efficiency when performing complex computations. However, hybrid quantum models, particularly on Quantum Convolutional Neural Networks (QCNNs) face two significant drawbacks: the placement of the quantum convolutional layer before the model architecture and the lack of integration of the quantum layer within the training process. These disadvantages reduce the robustness and reproducibility of the models. This study proposes that integrates the quantum layer into the quantum layer to address these shortcomings. We present a comparative analysis between a hybrid quantum deep learning model, which includes a trainable quantum layer, and its classical counterpart for the classification of skin cancer dermatoscopic images. The hybrid model attains 0.7865 of accuracy, a recall of 0.7321, a precision of 0.7268, and an F1 Score of 0.7288, while the classical model reaches an accuracy, recall, precision, and F1 Score of 0.8510, 0.8472, 0.8495, and 0.8447. The hybrid model achieves comparable results to its classical counterpart and demonstrates the advantages of weight adjustment in quantum layers and their potential in improving medical imaging analysis.
Open-source 3D-printed microscope with semiautomated liquid crystal polarizer setups: a new opportunity for detecting small phase retards in oocyte meiotic spindlesAlcalde, J. Jose; Restrepo-Martínez, Alejandro; Restrepo Betancur, Giovanni
doi: 10.1117/12.3028130pmid: N/A
A microscope design was developed using 3D printing and liquid crystals to achieve variable polarization configurations and semi-automatic processes without the need for mechanical movement of polarizers and retarders. The device includes a polariscope composed of electronically controlled liquid crystals and a compliant mechanism for precise micrometric movements. Stepper motors and software control these movements, and the process of acquiring images requires connecting a sensor to a Raspberry Pi. The microscope's lens and extension tube assembly magnify the image 600 times. The study compares two polarization techniques: Stokes and ellipsometric polarization. Additionally, it analyzes crystals and meiotic spindles of maturing porcine oocytes. The ellipsometric technique is more effective in detecting low retards, as indicated by the results. This prototype has the potential to reduce the cost of in vitro fertilization in assisted reproduction laboratories, with a focus on animals of high genetic value.
Understanding the degrees of freedom of wavefront modulation by liquid crystal on silicon microdisplay with a digital backplaneSánchez-Montez, A. R.; Francés, J.; Moya, A.; Mena, E. J.; Bravo, J. C.; Calzado, E. M.; Gallego, S.; Beléndez, A.; Márquez, A.
doi: 10.1117/12.3027529pmid: N/A
Digital backplane liquid crystal on silicon devices (LCoS) are widely used in wavefront engineering applications due the maturity of the technology, thus the reliability of their performance. A thorough study of the relation between the different control parameters and their effect on the retardance modulation is lacking though. These control parameters, which are the low and high levels of the voltage signal together with the grey level addressed, in relation with the retardance modulation produced are explored across the whole visible spectrum. From a more practical point of view, this enables to decide which voltage parameters across the whole range of possibilities are the most appropriate for a certain wavefront engineering problem without the need to measure them in advance. Additionally, we are interested in the comparison of two different approaches developed in our research group to obtain the retardance modulation to see their possible pros and cons. The results presented are backed by the experimental measurements provided.
Three-dimensional object texturing for visible-thermal fringe projection profilometersJuarez-Salazar, Rigoberto; Benjumea, Eberto; Marrugo, Andres G.; Diaz-Ramirez, Victor H.
doi: 10.1117/12.3028321pmid: N/A
Conventional fringe projection profilometers utilize cameras and projectors in the visible spectrum. Nevertheless, some applications require profilometers with a complementary thermal camera for the infrared spectrum. Since the point cloud is computed from pixel correspondences between the visible camera-projector pair, the texture in the visible spectrum is obtained by direct association of color from each image pixel to its corresponding point in the cloud. Unfortunately, the texture from the thermal camera is not straightforward because of the inexistence of pixel-point correspondences. In this paper, a simple interpolation-based method for determining the texture of the reconstructed objects is proposed. The theoretical principles are reviewed, and an experimental verification is conducted using a visible-thermal fringe projection profilometer. This work provides a helpful framework for three-dimensional data fusion for advanced multi-modal profilometers.
Enhancing sea turtle photo identification: a comparative analysis of a self-developed noninvasive automated algorithm versus the manual HotSpotter methodRios-Ramos, Arturo; García-Vázquez, Mireya Saraí; Ramírez-Acosta, Alejandro Álvaro
doi: 10.1117/12.3028422pmid: N/A
Accurate individual identification of animals plays a crucial role in population studies, providing invaluable insights for species research and conservation researchers. Such identification enables the tracking of migratory patterns, growth rates, and survival rates, which are essential for understanding species dynamics and implementing effective conservation strategies.In this work presents an AI-based approach for individual sea turtle identification using Photo-ID. Comparing an own-developed algorithm with the HotSpotter ID, a well-known method for semi-automated identification of individual sea turtles within populations, highlighting differences in image preprocessing and One-vs-Many matching evaluation. Tested on a diverse database of sea turtle images. The database images vary in environments, light conditions, qualities and resolutions, at different distances, and angles. The proposed Photo-ID method involves automatic detection of the turtle’s head using a modified YOLOv5 network, extraction of pixels to emphasize head scale patterns, and the ORB algorithm for identification. With standard quality images, the proposed algorithm achieves 98% accuracy and add an end-to-end pipeline to the photoidentification process, outperforming the HotSpotter’s 96% and required for human intervention. This approach enhances the identification process, contributing to endangered species protection and addressing the challenges associated with the time-consuming nature of traditional Photo-ID methods.
Holographic mirror-based approach in augmented reality glassesMárquez, A.; García-Vázquez, J. C.; Bravo, J. C.; Francés, J.; Neipp, C.; Gallego, S.; Ortuño, M.; Ramírez, M. G.; Pascual, I.; Beléndez, A.
doi: 10.1117/12.3029958pmid: N/A
In the last years many efforts have been invested in the development of augmented reality devices. Depending on the application different constraints need to be faced. Providing full color see-through augmented reality on eyeglasses with ophthalmic correction, and valid for a wide range of use cases, is one of the most challenging and ambitious applications. We are within a European Project aiming to this goal. One of the key components in this eyewear is the holographic lens mirror (HLM), acting as the beam combiner responsible for the see-through capability. In this work, we present the main goals of this European Project and, more specifically, the holographic approach being developed for the HLM within our research group.
LiDAR-based classification of objects and terrainGarcía, Andrés; Martínez, Brandon; Moroyoqui, Zaid; Picos, Kenia; Orozco-Rosas, Ulises
doi: 10.1117/12.3028632pmid: N/A
This paper presents the development of a LiDAR-based object classification system using machine learning and signal processing. The proposal explores Support Vector Machines (SVM) and neural networks to classify terrain with the help of a LiDAR that scans an area similarly to how a picture is taken. This project involves the processing of data to generate a point cloud that lets us visualize the scans taken by the Light Detection and Ranging (LiDAR). The dataset was built by taking multiple scans of three types of terrain, flat, grassy, and rocky. This paper shows experimental results of machine learning models built around LiDAR-acquired data and small datasets, it also shows point cloud visualizations and a simple signal processing technique.