Artificial neural networks can solve various tasks in computer vision, such as image classification, object detection, and general recognition. Our comparative study deals with four types of ...artificial neural networks—multilayer perceptrons, probabilistic neural networks, radial basis function neural networks, and convolutional neural networks—and investigates their ability to classify 2D matrix codes (Data Matrix codes, QR codes, and Aztec codes) as well as their rotation. The paper presents the basic building blocks of these artificial neural networks and their architecture and compares the classification accuracy of 2D matrix codes under different configurations of these neural networks. A dataset of 3000 synthetic code samples was used to train and test the neural networks. When the neural networks were trained on the full dataset, the convolutional neural network showed its superiority, followed by the RBF neural network and the multilayer perceptron.
Convolutional neural networks are special types of artificial neural networks that can solve various tasks in computer vision, such as image classification, object detection, and general recognition. ...The paper presents the basic building blocks of convolutional neural networks and their architecture, and compares their recognition accuracy with other character recognition techniques using the example of character recognition from vehicle registration plates. The purpose of the experiments was to determine the optimal configuration of the convolutional neural network and the influence of the size and design method of the training set on the recognition rate. The study shows that although convolutional neural networks have recently gained attention, traditional recognition methods are still relevant, and the choice of the right classifier and its configuration depends on the type of recognition task.
QR (quick response) Codes are one of the most popular types of two-dimensional (2D) matrix codes currently used in a wide variety of fields. Two-dimensional matrix codes, compared to 1D bar codes, ...can encode significantly more data in the same area. We have compared algorithms capable of localizing multiple QR Codes in an image using typical finder patterns, which are present in three corners of a QR Code. Finally, we present a novel approach to identify perspective distortion by analyzing the direction of horizontal and vertical edges and by maximizing the standard deviation of horizontal and vertical projections of these edges. This algorithm is computationally efficient, works well for low-resolution images, and is also suited to real-time processing.
Wood has been widely used as a building and interior furniture decoration material due to its excellent insulation of heat and electricity, strong buffer effect on vibration, high strength, etc. ...Generally, wood materials should be processed by pyrolysis technique in order to improve corrosion resistance, flame retardancy, and dimensional stability. However, during pyrolysis, the main components of wood, such as cellulose, hemicellulose, and lignin, undergo chemical reactions causing the damage of the internal structure. With existing non-destructive evaluation methods, such as thermography and radiography, it is difficult to detect the degree of delamination within the wood due to its anisotropy physical properties and complex internal structure. In this work, a novel normalized time-domain integration method is proposed to detect the delamination of wood materials at different pyrolysis temperatures. The experimental results show the great robustness and detection efficiency of this method. Furthermore, numerical simulation and experiments are used to build the relationship between the terahertz time-domain signal and water content. Compared with spruce and oak, meranti is more resistant to pyrolysis and has higher structural stability.
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•The variations of several parameters are discussed at different pyrolysis T °C.•The amplitude at a specific frequency is used to characterize the water content in the woods.•Numerical simulation and experiments validated the feasibility of the proposed new evaluation technique.•A novel normalized time-domain integration (NTDI) method is proposed for the inspection of internal delamination.•All the woods are detected using NTDI method and X-ray photography.
We provide a comprehensive and in-depth overview of the various approaches applicable to the recognition of Data Matrix codes in arbitrary images. All presented methods use the typical “L” shaped ...Finder Pattern to locate the Data Matrix code in the image. Well-known image processing techniques such as edge detection, adaptive thresholding, or connected component labeling are used to identify the Finder Pattern. The recognition rate of the compared methods was tested on a set of images with Data Matrix codes, which is published together with the article. The experimental results show that methods based on adaptive thresholding achieved a better recognition rate than methods based on edge detection.
The monitoring of heritage objects is necessary due to their continuous deterioration over time. Therefore, the joint use of the most up-to-date inspection techniques with the most innovative data ...processing algorithms plays an important role to apply the required prevention and conservation tasks in each case study. InfraRed Thermography (IRT) is one of the most used Non-Destructive Testing (NDT) techniques in the cultural heritage field due to its advantages in the analysis of delicate objects (i.e., undisturbed, non-contact and fast inspection of large surfaces) and its continuous evolution in both the acquisition and the processing of the data acquired. Despite the good qualitative and quantitative results obtained so far, the lack of automation in the IRT data interpretation predominates, with few automatic analyses that are limited to specific conditions and the technology of the thermographic camera. Deep Learning (DL) is a data processor with a versatile solution for highly automated analysis. Then, this paper introduces the latest state-of-the-art DL model for instance segmentation, Mask Region-Convolution Neural Network (Mask R-CNN), for the automatic detection and segmentation of the position and area of different surface and subsurface defects, respectively, in two different artistic objects belonging to the same family: Marquetry. For that, active IRT experiments are applied to each marquetry. The thermal image sequences acquired are used as input dataset in the Mask R-CNN learning process. Previously, two automatic thermal image pre-processing algorithms based on thermal fundamentals are applied to the acquired data in order to improve the contrast between defective and sound areas. Good detection and segmentation results are obtained regarding state-of-the-art IRT data processing algorithms, which experience difficulty in identifying the deepest defects in the tests. In addition, the performance of the Mask R-CNN is improved by the prior application of the proposed pre-processing algorithms.
The relationship between wood and its degree of humidity is one of the most important aspects of its use in construction and restoration. The wood presents a behavior similar to a sponge, therefore, ...moisture is related to its expansion and contraction. The nondestructive evaluation (NDE) of the amount of moisture in wood materials allows to define, e.g., the restoration procedures of buildings or artworks. In this work, an integrated study of two non-contact techniques is presented. Infrared thermography (IRT) was able to retrieve thermal parameters of the wood related to the amount of water added to the samples, while the interference pattern generated by speckles was used to quantify the expansion and contraction of wood that can be related to the amount of water. In twenty-seven wooded samples, a known quantity of water was added in a controlled manner. By applying advanced image processing to thermograms and specklegrams, it was possible to determine fundamental values controlling both the absorption of water and the main thermophysical parameters that link the samples. On the one hand, results here shown should be considered preliminary because the experimental values obtained by IRT need to be optimized for low water contents introduced into the samples. On the other hand, speckle interferometry by applying an innovative procedure provided robust results for both high and low water contents.
QR (Quick Response) codes are one of the most famous types of two-dimensional (2D) matrix barcodes, which are the descendants of well-known 1D barcodes. The mobile robots which move in certain ...operational space can use information and landmarks from environment for navigation and such information may be provided by QR Codes. We have proposed algorithm, which localizes a QR Code in an image in a few sequential steps. We start with image binarization, then we continue with QR Code localization, where we utilize characteristic Finder Patterns, which are located in three corners of a QR Code, and finally we identify perspective distortion. The presented algorithm is able to deal with a damaged Finder Pattern, works well for low-resolution images and is computationally efficient.
Data Matrix codes can be a significant factor in increasing productivity and efficiency in production processes. An important point in deploying Data Matrix codes is their recognition and decoding. ...In this paper is presented a computationally efficient algorithm for locating Data Matrix codes in the images. Image areas that may contain the Data Matrix code are to be identified firstly. To identify these areas, the thresholding, connected components labelling and examining outer bounding-box of the continuous regions is used. Subsequently, to determine the boundaries of the Data Matrix code more precisely, we work with the difference of adjacent projections around the Finder Pattern. The dimensions of the Data Matrix code are determined by analyzing the local extremes around the Timing Pattern. We verified the proposed method on a testing set of synthetic and real scene images and compared it with the results of other open-source and commercial solutions. The proposed method has achieved better results than competitive commercial solutions.
The paper focuses on the use of holographic interferometry in the research of thermal modification and its effect on the heat transfer from the wood surface to the surrounding air. In the experiment, ...spruce wood samples modified at 160 °C, 180 °C, 200 °C, 220 °C and an unmodified control sample were used. A radiant heat source was placed under the sample. The top of the sample represented the boundary where the observed heat transfer occurred. The temperature fields above the sample were visualized by real-time holographic interferometry and the heat transfer coefficient α was calculated from the obtained interferograms. During the heating of the samples, a decrease of the heat transfer coefficient was observed. The heat transfer coefficient of the control unmodified sample decreased from a maximum of α = 22.66 Wm–2K–1 to a minimum of α = 8.6 Wm–2K–1. In comparison with these values, the heat transfer coefficients of the modified samples treated at 160, 180, 200 and 220 °C, respectively, decreased to 99%, 93%, 68% and 51% of the maximal control value at the beginning of experiment and to 95%, 86%, 80% and 64% of the minimal control value by the end of the experiment. Moreover, an analysis of variance was used to determine the significance of the heat treatment effect on the heat transfer coefficient. A high significance (p < 5%) was observed between the control sample and the modified samples treated at 200 °C and 220 °C. Experiments with the use of holographic interferometry produced results consistent with previous studies conducted by different methods.
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