Abstract

This article describes an image processing system based on an intelligent ad-hoc camera, whose two principle elements are a high speed 1.2 megapixel Complementary Metal Oxide Semiconductor (CMOS) sensor and a Field Programmable Gate Array (FPGA). The latter is used to control the various sensor parameter configurations and, where desired, to receive and process the images captured by the CMOS sensor. The flexibility and versatility offered by the new FPGA families makes it possible to incorporate microprocessors into these reconfigurable devices, and these are normally used for highly sequential tasks unsuitable for parallelization in hardware. For the present study, we used a Xilinx XC4VFX12 FPGA, which contains an internal Power PC (PPC) microprocessor. In turn, this contains a standalone system which manages the FPGA image processing hardware and endows the system with multiple software options for processing the images captured by the CMOS sensor. The system also incorporates an Ethernet channel for sending processed and unprocessed images from the FPGA to a remote node. Consequently, it is possible to visualize and configure system operation and captured and/or processed images remotely.

Highlights

  • These days there are numerous situations where one or several machine vision cameras are routinely used to make daily life more comfortable

  • We present a solution aimed at integrating hardware and software processing in the same device, a SCVX4 camera

  • The remainder of the article is divided into the following sections: Section 2, which reviews some of the most important studies regarding Field Programmable Gate Array (FPGA) image processing; Section 3, which presents the most relevant characteristics of Complementary Metal Oxide Semiconductor (CMOS) and Charged Coupled Device (CCD) sensors; Section 4, which details the structure of the design presented here; Section 5, which gives the most significant results obtained in this study, and lastly; Section 6, which summarizes the most important conclusions

Read more

Summary

Introduction

These days there are numerous situations where one or several machine vision cameras are routinely used to make daily life more comfortable. The system proposed was validated at architectural level, optimizing the datapath and different pipelines for each design block It was not the aim of this study to implement novel image processing, and the camera implemented image processing based on singular value thresholding, which enabled us to validate the present proposal. With this system, thresholding can be implemented on the hardware or the software block in order to compare the different implementations at the same time as validating the intelligent camera architecture. The remainder of the article is divided into the following sections: Section 2, which reviews some of the most important studies regarding FPGA image processing; Section 3, which presents the most relevant characteristics of CMOS and CCD sensors; Section 4, which details the structure of the design presented here; Section 5, which gives the most significant results obtained in this study, and lastly; Section 6, which summarizes the most important conclusions

Related Studies
APTIMA CMOS Sensors
Sending processing results stage
Results
Conclusions
Datasheets
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call