Leaf Area Index (LAI) holds significant importance as a specific characteristic of Leaf Areas in the field of smart agriculture. This study explores the estimation of LAI using a multi-spectral image from WorldView 3 ...
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ISBN:
(纸本)9798350386202;9798350386196
Leaf Area Index (LAI) holds significant importance as a specific characteristic of Leaf Areas in the field of smart agriculture. This study explores the estimation of LAI using a multi-spectral image from WorldView 3 satellite. The image combines 8 VNIR bands and has a spatial resolution of 1.24m. To overcome the limited amount of available data, the image was split into smaller subsets called paxels, resulting in 500 paxels for training and testing. For enhancing machine learning models. performance, the standardisation of a dataset is made, after that, a Multilayer Perceptron with a specific architecture aimed to predict LAI from the multiple bands is trained. The achieved results showed promising performance in LAI prediction. Overall, the study demonstrates the potential of using satellite imagery and machine learning algorithms to improve our understanding of crop health and productivity.
Illegal trade and theft of coins appears to be a major part of the illegal antiques market. image based recognition of coins could substantially contribute to fight against it. Central component in the permanent ident...
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a kind of spatial-temporal neural network video smoke detection algorithm is proposed in order to solve the problems associated with the incorrect classification of the static approximate smoke background in the face ...
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With the rise in clinicopathologic prognosis and the introduction of whole slide imaging scanners, artificial intelligence systems are being suggested to assist pathologists in their decision-making processes. Despite...
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This paper addresses two problems commonly associated with video target tracking system. First, video target detection and tracking usually require extensive searching in a large space to find the best matches for pre...
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ISBN:
(纸本)9780819471598
This paper addresses two problems commonly associated with video target tracking system. First, video target detection and tracking usually require extensive searching in a large space to find the best matches for preregistered templates. Existing fast search methods cannot guarantee a global optimal match, which results in substandard performance. To obtain a true global match, a full search at the pixel or sub-pixel level is required. Obviously., this introduces significant computational overhead, which limits the implementation of these algorithms in real-time applications. In this paper, we propose a fast method to compute two-dimensional normalized cross-correlations to efficiently find the global optimal match result from a large image area. Comparisons and complexity analysis are provided to show the efficiency of the proposed algorithm. Second, another challenge commonly faced by detection and tracking systems is the accurate detection of target orientation in a two-dimensional image. This problem is motivated by applications where the walk-in and walk-out people need to be detected and a fast image registration method is needed to compensate the change in rotation, translation and size, which is natural since the target's distance from the camera is changing dramatically. To address this issue, we propose a novel and efficient eigenvector-based method to detect target orientation and apply it into automatic human recognition system. Experimental and real-world test results verify that the proposed fast algorithm achieves similar accuracy as the recursive registration method which is computationally expensive.
Ultrasound imaging uses high-frequency sound waves in medical imaging like obstetric diagnosis, stones in kidney etc. As ultrasound images are captured in real-time, they can show movement of the body's internal o...
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ISBN:
(纸本)9781479956906
Ultrasound imaging uses high-frequency sound waves in medical imaging like obstetric diagnosis, stones in kidney etc. As ultrasound images are captured in real-time, they can show movement of the body's internal organs as well as blood flowing through blood vessels. In this paper medical B-mode architecture of the backend system is implemented in Kintex-7 FPGA platform. The backend processing consists of envelope detection which uses fixed filter coefficients for Hilbert transformation, log compression technique to achieve the desired dynamic range for display and image enhancement technique to increase the contrast. In-phase and quadrature phase components are computed using envelope detection block, whose absolute value is compressed to fit the dynamic range of display and interpolated to avoid artifacts while displaying. Further full scale contrast stretch enhancement technique is used to improve the image clarity. The implementation of the backend algorithms along with image enhancement technique on FPGA, show that the resolution of display is improved and also the hardware resource utilization is minimized leading to compact design for portable ultrasound systems.
Currently, carpet companies assess the quality of their products based on their appearance retention capabilities. For this, carpet samples with different degrees of wear after a traffic exposure simulation process ar...
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ISBN:
(纸本)9780819484079
Currently, carpet companies assess the quality of their products based on their appearance retention capabilities. For this, carpet samples with different degrees of wear after a traffic exposure simulation process are rated with wear labels by human experts. Experts compare changes in appearance in the worn samples to samples with original appearance. This process is subjective and humans can make mistakes up to 10% in rating. In search of an objective assessment, research using texture analysis has been conducted to automate the process. Particularly, Local Binary Pattern (LBP) technique combined with a Symmetric adaptation of the Kullback-Leibler divergence (SKL) are successful for extracting texture features related to the wear labels either from intensity and range images. We present in this paper a novel extension of the LBP techniques that improves the representation of the distinct wear labels. The technique consists in detecting those patters that monotonically change with the wear labels while grouping the others. Computing the SKL from these patters considerably increases the discrimination between the consecutive groups even for carpet types where other LBP variations fail. We present results for carpet types representing 72% of the existing references for the EN1471:1996 European standard.
To improve the performance of remote sensing images multiclass classification we propose two greedy algorithms of feature selection. The discriminant analysis criterion and regression coefficients are used as the meas...
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This research focuses on comparing the classification performance of Local Mean-based K Nearest Neighbors (LMKNN) using different distance metrics. Specifically, we examine different value of close neighbors and 10 di...
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Wavefront coding (WFC) uses a special aspheric optics and digital imageprocessing to extend the depth of focus in imaging systems. An intermediate blurred image is generated by the spatial convolution of the image wi...
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ISBN:
(纸本)9781628412192
Wavefront coding (WFC) uses a special aspheric optics and digital imageprocessing to extend the depth of focus in imaging systems. An intermediate blurred image is generated by the spatial convolution of the image with the point spread function (PSF) of a cubic phase mask. Restoration tests are performed on an optically encoded image. The best option to restore an image is not always given by a deconvolution method using the PSF of the imaging system. Due to it is limited by the perfect PSF of the system. In this study, the restored image is given by a deconvolution method using the numerical PSF. As the quality of the image is depended of the pupil diameter and strength of the wfc phase plate, an optimization was achieved by means of measuring the decoded image contrast. Results shows a high resolution decoded image.
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