KEYWORDS: Image processing, Field programmable gate arrays, Fuzzy logic, RGB color model, Image classification, Digital filtering, Image filtering, Classification systems, Digital image processing, Binary data
Most of the methods surveyed for detecting moving objects through image processing in general purpose processors (GPPs) presented an approach that did not allow successful implementation in field programmable gate array (FPGA). The correct classification of the pixels in these methods is directly related to the need for many resources in terms of memory due to the complex mechanism to get the reference image. Additionally, almost all the methods analyzed used only conventional techniques of digital image processing (DIP). Thus, we propose an approach that combines conventional techniques of DIP with fuzzy integral in a parallel processing aiming to improve the detection of moving vehicles. Hence, the proposed decision-making system seeks not to compromise results in terms of pixel classification even by implementing a simple modeling mechanism. Results in terms of occupied resource, maximum operating frequency, and pixel classification are verified in low-cost FPGA-based implementation. The proposed system processes the images in real-time and presents better pixel classification than just fuzzy decision-making.
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