KEYWORDS: Image processing, Field programmable gate arrays, Data modeling, Digital signal processing, Binary data, MATLAB, Simulink, Image processing algorithms and systems, Image segmentation, Cameras
The task of image fragments extraction with objects of interest is not new. The choice of appropriate segmentation algorithm and its implementation in real time mode become a problem in systems operating with a high-speed video data stream. Connected components labeling is an important step in training samples images preparation for usage in neural networks. To ensure high speed and feasibility of image labeling algorithm for the FPGA, it is necessary to justify the choice of segmentation algorithms, considering the hardware capabilities of the platform. In this paper, we propose a modified one-pass image labeling algorithm for FPGAs, as well as its implementation using the Xilinx System Generator for DSP and the Matlab/Simulink package. As a hardware platform the FMC-200-A mezzanine is used to provide high-speed video data stream from the line camera TELEDYNE DALSA LA-CC-04K05B00-R to the ZYNQ Ultrascale + MPSoC ZCU106 evaluation kit board. The procedure of using hardware implemented SPI interface on the MPSoC ZCU106 board, which is to configure and control the FMC200-A module is described. Implementation of SPI interface is made by using Vivado and Vitis IDE. The labeling results of proposed algorithm on test images, as well as images obtained experimentally are presented.
The high quality of seed cleaning is one of the factors in increasing the yield of agricultural crops. To improve its quality, it is important to estimate average size of seeds for adjusting their feeding method into analysis zone of the optical seeds sorter (the color sorter). Optical methods for average seed size measuring have a significant drawback, which consists in usage of video camera, which lens must be periodically cleaned from settling dust. An alternative method for estimating size of crop seeds is the use of millimeter-wave radar. To assess the geometric characteristics of seeds, it is proposed to use adapted algorithms for sea surface remote sensing. The possibility of applying remote sensing algorithms to the seed layer is justified due to the similarity of geometric structure of the seed layer with a quasi-periodic surface, which is the sea surface. This article discusses an approach for seeds layer spatial model obtaining. The description of backscattered radar signal model is given. We carried out the modeling data analysis and a comparison of estimated average seed size with the geometric characteristics of the layer for different crops. Obtained model results allow us to conclude about the applicability of remote sensing algorithms for geometric characteristics of seeds estimation. Usage of radar data acquisition methods allows to use the available in market mmWave solutions to reduce the cost of measuring equipment for geometric characteristics of seeds for various crops.
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