In image processing applications, soft mathematical morphology (MM) can be employed for both binary and grayscale systems and is derived from set theory. Soft MM techniques have improved behavior over standard morphological operations in noisy environments, as they can preserve small details within an image. This makes them suitable for use in image processing applications on portable field programmable gate arrays for tasks such as robotics and security. We explain how the systems were developed using Altera’s DSP Builder in order to provide optimized code for the many different devices currently on the market. Also included is how the circuits can be inserted and combined with previously developed work in order to increase their functionality. The testing procedures involved loading different images into these systems and analyzing the outputs against matlab-generated validation images. A set of soft morphological operations are described, which can then be applied to various tasks and easily modified in size via altering the line buffer settings inside the system to accommodate a range of image attributes ranging from image sizes such as 320×240 pixels for basic webcam imagery up to high quality 4000×4000 pixel images for military applications.
KEYWORDS: Video, Image processing, Clocks, Video processing, Imaging systems, Cameras, Field programmable gate arrays, Data processing, Control systems, Process control
Recent advances in semiconductor technology have made it possible to integrate an entire system including processors, memory, and other system units into a single programmable chip [a field programmable gate array (FPGA)]. These configurations, called system on a programmable chip (SOPC), have the advantage of being designed and implemented quicker than traditional technologies and are relatively cheap to produce for low volume applications. One processor-intensive application, which is ideal for SOPC technology, is that of image processing where there is a repeated application of operations on the two-dimensional data. We present the results of research that investigate the use of SOPC technology in building a real-time image-processing system with the capability of performing video acquisition, image processing, and image display. In order to solve the complex on-chip data communication, while not degrading the transfer speed of large amounts of video data, a novel and effective bus arbitration solution called “simultaneously multimastering Avalon streaming transfer with peripheral-controlled waitrequest” is developed. Rather than using the software approach to initialize direct memory access (DMA) like transfers, this solution takes advantage of the FPGA hardware resources to perform bus arbitration and hence increase system efficiency.
KEYWORDS: Digital watermarking, Digital signal processing, Image processing, Binary data, Sensors, Digital image processing, Information security, Multimedia, Digital imaging, Field programmable gate arrays
Digital image watermarking is the process of embedding information into a digital image which may be used to verify its
authenticity or the identity of its owners. This is the same as paper bearing a watermark for visible identification such as
in money for example. In digital watermarking, if the signal is copied, then the information also is carried in the copy,
proving that the data has been copied. In this paper, a digital watermarking approach is investigated using the DSP
Builder methodology in order to provide the Morphological Scene Change Detector (MSCD) with a means by which if it
detects an intruder, a watermarked copy of the triggering image is produced. This is so that if the image is required as
proof in a court case; it can help show that the image has not been tampered with by means of the watermark. The system
uses an 8-bit greyscale image and maps a binary watermark image onto the lowest bit level; this is then used when the
MSCD is triggered. For simplicity in this case, the watermark image is the same size and the target image to be
watermarked, future variations with foresee a variable watermark image size. The result will be a watermarked image
that if a section is copied and pasted into another file and that file is then analysed, the watermark will be visible. The
process of integrating the watermarking process into the MSCD will also be discussed as this system originally used
binary images to speed up the process. Finally, this watermark system can be used with any system designed as all that is
required is to insert the sub-system into a larger system meaning that it is extremely interchangeable.
Keywords: Digital Watermarking, Scene Change Detection, FPGA, DSP Builder.
Vector analysis is a well-developed field that deals with details about line, surface and volume integrals which can be
solved analytically to provide solutions to many problems. Using vector analysis, a curve can be divided up into many
small arcs, each of which is a position vector. The summation of these position vectors can be used to represent the curve
in detail; this is known as the total vector field. In this paper, there is shown a vector analysis methodology when applied
to the wake immediately after a moving or stationary object, caused by the movement of the object through free space or
the surrounding medium moving around the object respectively. The aim was to create a system that can determine the
vectors between successive images in a video with the end result being able to establish an overall trajectory of the
object. This could be implemented on a Field Programmable Gate Array (FPGA) or other device to be deployed in the
field to track any type of object. If the device’s orientation with magnetic north-south is known, the direction of the
object is travelling in can be calculated and then relayed on. This could be useful as an easily deployable warning system
for the armed forces or rescue services to inform personnel of potential incoming threats. This work builds upon the
Morphological Scene Change Detection (MSCD) mechanism implemented in the DSP Builder environment and
describes how the changes allow the system to track the wake and plot its trajectory. System simulations of real world
data are shown and the resultant imagery is then discussed. Furthermore, tests are conducted on single objects and then
multiple objects to investigate how the system responds as real world situations are likely to have more than a single
object.
Morphological Scene Change Detection (MSCD) systems can be used to secure environments by sensing potential intruders and alerting security personnel to any security risks. To achieve this, the system compares the input from a
camera to a reference image quantifying the level of change between the images, raising the alarm if this change is
greater than a set triggering level. Morphological operators are than used to reduce the effect of any image change not related to a potential security risk; this includes noise and other minor changes thus decreasing the risk of false alarms. However in low light conditions MSCD systems can fail due to the reduced intensity differences between images containing security threats and reference images. This paper documents a proof of concept for a system that would use night vision images to address this problem. Here a low light scope camera attachment is used in place of a night vision camera and shows modifications to the previous MSCD system, which improves the performance when used with night vision images. The analysis of the modified system’s performance in different low light environments, this includes analysis of appropriate binary threshold and alarm triggering levels for a range of environments. The latter includes indoors at a distance, indoors at close range, outdoors at a distance and outdoors at close range. The results shown demonstrate that MSCD systems operating in low light conditions have the potential to be used as a useful tool in a security system and are compared to the original to demonstrate the improvement.
This paper focuses on the development of a portable variable climate controlled system that can be tailored to the
requirements of the item to be stored by manipulating the temperature, humidity and light levels within the controlled
area. This could be used to store anything from bio-chemical samples (to preserve them from field work) to cooled
electronics (prior to deployment in a given situation) to foodstuffs (such as wine and other alcohols). In this situation
however, to provide a relatively simplistic example, the environment will be used to store wine. The system is adaptive
in that anything can be stored within it, assuming the storage parameters are known in order to correctly configure the
environment. In this paper a microcontroller (PICF4520) is connected to a fridge with various sensors attached to
monitor and manipulate the environment and adjust it accordingly. For the chosen item to be stored, a temperature of 13-
14oC is required, a high humidity level and a non-Ultraviolent (UV) light source. This work thus allows for a small
handheld unit that could be used to control the climate within without the need for the traditional 12 – 16 foot size
portable units traditionally used. The unit could be left in the field and run off a solar cell to assist in longer term studies.
This paper presents how the microcontroller is connected to the fridge and its sensors, how it manipulates the
environment and the process by which the temperature and other factors can be changed without having to edit and recompile
the C code, this allows for a much more friendly device interface.
KEYWORDS: Digital signal processing, Navigation systems, Sensors, Field programmable gate arrays, Buildings, MATLAB, Visualization, Filtering (signal processing), Clocks, Mobile robots
Dead Reckoning (DR) is the process of estimating a robot's current position based upon a previously determined
position, and advancing that position based upon known speed and direction over time. It is therefore a simple way for an
autonomous mobile robot to navigation within a known environment such as a building where measurements have been
taken and a predetermined route planned based upon which doors (or areas) the robot would have enough force to enter.
Discussed here is the design of a DR navigation system in Altera's DSP Builder graphical design process. The wheel
circumference to the step size of stepper motor used to drive the robot are related and so this ratio can be easily changed
to easily accommodate changes to the physical design of a robot with minimal changes to the software. The robot
calculates its position in relation to the DR map by means of the number of revolutions of the wheels via odometry, in
this situation there is no assumed wheel slippage that would induce an accumulative error in the system overtime. The
navigation works by using a series of counters, each corresponding to a measurement taken from the environment, and
are controlled by a master counter to trigger the correct counter at the appropriate time given the position of robot in the
DR map. Each counter has extra safeguards built into them on their enables and outputs to ensure they only count at the
correct time and to avoid clashes within the system. The accuracy of the navigation is discussed after the virtual route is
plotted in MATLAB as a visual record in addition to how feedback loops, identification of known objects (such as fire
safety doors that it would navigate through), and visual object avoidance could later be added to augment the system.
The advantages of such a system are that it has the potential to upload different DR maps so that the end robot for can be
used in new environments easily.
Morphological Scene Change Detection (MSCD) is a process typically tasked at detecting relevant changes in a guarded
environment for security applications. This can be implemented on a Field Programmable Gate Array (FPGA) by a
combination of binary differences based around exclusive-OR (XOR) gates, mathematical morphology and a crucial
threshold setting. The additional ability to set up the system in virtually any location due to the FPGA makes it ideal for
insertion into an autonomous mobile robot for patrol duties. However, security is not the only potential of this robust
algorithm. This paper details how such a system can be used for the detection of leaks in piping for use in the process
and chemical industries and could be deployed as stated in the above manner. The test substance in this work was water,
which was pumped either as a liquid or as low pressure steam through a simple pipe configuration with holes at set
points to simulate the leaks. These holes were situated randomly at either the center of a pipe (in order to simulate an
impact to it) or at a joint or corner (to simulate a failed weld). Imagery of the resultant leaks, which were visualised as
drips or the accumulation of steam, which where analysed using MATLAB to determine their pixel volume in order to
calibrate the trigger for the MSCD. The triggering mechanism is adaptive to make it possible in theory for the type of
leak to be determined by the number of pixels in the threshold of the image and a numerical output signal to state which
of the leak situations is being observed. The system was designed using the DSP Builder package from Altera so that its
graphical nature is easily comprehensible to the non-embedded system designer. Furthermore, all the data from the DSP
Builder simulation underwent verification against MATLAB comparisons using the image processing toolbox in order to
validate the results.
KEYWORDS: Cameras, Stereo vision systems, Imaging systems, Digital signal processing, Field programmable gate arrays, Simulink, Robotics, Control systems, Servomechanisms, Visual process modeling
Stereo vision is a situation where an imaging system has two or more cameras in order to make it more robust
by mimicking the human vision system. By using two inputs, knowledge of their own relative geometry can
be exploited to derive depth information from the two views they receive. 3D co-ordinates of an object in an
observed scene can be computed from the intersection of the two sets of rays. Presented here is the development
of a stereo vision system to focus on an object at the centre of a baseline between two cameras at varying
distances. This has been developed primarily for use on a Field Programmable Gate Array (FPGA) but an
adaptation of this developed methodology is also presented for use with a PUMA 560 Robotic Manipulator with
a single camera attachment. The two main vision systems considered here are a fixed baseline with an object
moving at varying distances from this baseline, and a system with a fixed distance and a varying baseline. These
two differing situations provide enough data so that the co-efficient variables that determine the system operation
can be calibrated automatically with only the baseline value needing to be entered, the system performs all the
required calculations for the user for use with a baseline of any distance. The limits of system with regards to
the focusing accuracy obtained are also presented along with how the PUMA 560 controls its joints for the stereo
vision and how it moves from one position to another to attend stereo vision compared to the two camera system
for the FPGA. The benefits of such a system for range finding in mobile robotics are discussed and how this
approach is more advantageous when compared against laser range finders or echolocation using ultrasonics.
The Charpy impact test technique assesses the toughness of an engineering material. The test measures the amount of energy a specimen can resist before it is broken by the impact of a heavy pendulum. Estimation of toughness is carried out manually by a skilled operator; they assess the percentage of light-reflective brittle regions on the fracture area. Because this assessment is performed manually, there is some subjectivity in the results. This study proposes a machine-based-learning algorithm to estimate this measure automatically. The method consists of capturing a digital image of the fracture surface after impact, preprocessing it, dividing it up into 10×10 pixel segments, and extracting from each segment features associated with its texture. Feature vectors feed a classifier whose purpose is to distinguish between brittle and ductile images (binary output). To estimate toughness, the classifier's outputs are used to construct a binary image, which is postprocessed to determine the percentage of the brittle region. To assess the accuracy of the algorithm, automatically and manually classified images are compared. Results show that the algorithm proposed was able to distinguish between brittle and ductile regions successfully and could be used instead of the manually performed technique.
KEYWORDS: Binary data, Image encryption, Field programmable gate arrays, Digital signal processing, Image processing, Computer security, Steganography, Digital watermarking, Defense and security, MATLAB
In this paper, we discuss a Field Programmable Gate Array (FPGA) implementation of steganography for
security applications such as anti-theft systems and forensic investigation systems. Our proposed method takes
advantage of both conventional encryption/decryption algorithms and fragile image watermarking techniques to
provide user-friendly interface. It could potentially be of benefit to financial investment companies, the military
and security forces in order to keep certain information hidden within other content with a change so subtle that
no one who does not know exactly where or how to look will not be able to obtain the data. In our proposed
system, a steganographic message known as plaintext is first encrypted by conventional methods to give an extra
layer of security, producing a ciphertext. The steganographic message can be either an image or ASCII text,
both of which will be discussed. Then, the cover text or image is modified to contain the ciphertext, yielding
a encrypted text or a watermarked image. Details of the circuitry for each stage are given with some of the
encryption and randomization circuitry not included in full detail for commercial reasons. Test images before
and after watermarking will be shown to demonstrate the validity and effectiveness of the proposed system.
Presented in this paper are the designs of several algorithms which enable the identification and tracking of
various regions within a series of images using FPGA technology. Two example probLem domains in the areas
of plasma physics and observational astronomy have been expolored. In the plasma physics application, an
initial pixel extraction technique has been expanded to include spatial (related to the distance from a cathode)
and value measurements (based on intensity values), which are subsequently merged in order to identify different
intensity / emissivity regions within a plasma assisted deposition system. The optimum combination of these and
other techniques are discussed, together with their reasons for selection. The control signals, decoding method
and subsequent processing steps, associated with how a point within individual images is selected, will also be
presented. In the astronomical application, a variation of a scene change detection mechanism is shown and how
this system was adapted in order to track and chart the motion of Near-Earth Objects (NEOs).
The charpy impact is a technique used to evaluate the toughness of an engineering material that determines the
amount of energy absorbed by it during fracture. Initially, measurements were estimated manually and later
replaced by a PC version. This study reports the development of the Field Programmable Gate Array (FPGA)
portable version. The FPGA based version allows easy analysis of samples without the need of sending them to
a lab for analysis. The process, presented here, as the original, is based on measuring the percent of crystal in
the test sample after impact, to determine if the material is ductile or brittle. The FPGA version, adapted under
the MATLAB Simulink environment, shows a graphical block representation of the charpy impact PC version.
An important asset of the FPGA version is its portability, it has to be easily modified and downloaded onto a
device to estimate the percent of brittle fracture of the broken Charpy surface. The beauty of the DSP Builder
programme is that it allows the model to be compiled to various types of optimised code for any Altera FPGA
device. To provide a firm basis for scientific comparison to the new FPGA system, images already analysed via
the PC based Java system were also used for testing and comparison purposes. The FPGA system converts the
image into an 8 bit grayscale image and analyses it in a 5x5 sampling window. This produces texture features
that can be used in a comparison system, similar to the Support Vector Machine (SVM) used in the original.
The output is a signal that states the material being tested is brittle or not via an output of '1' for brittle and
a '0' for ductile. A detailed pixel by pixel analysis of the various output images is then investigated to state the
percentage difference between the PC and FPGA based systems.
KEYWORDS: Image processing, Binary data, Control systems, Field programmable gate arrays, Signal processing, MATLAB, Digital signal processing, Molybdenum, Image filtering, Logic devices
In this paper, there are details of the continuation of the development of the previously designed multifunctional
morphological system and a description of how the system has been upgraded by including soft morphological
operators as their ability to compensate for noise by varying the k-value of the system and how this is of great
importance in image processing. This paper will cover the details of the upgrade process to include a greater
number of logical functions than its predecessor, how a biasing system was included to brighten or dim a certain
quadrant of the image or the entire image, how images are combined in either a product, mathematical or logical
block and finally how the control mechanism is interfaced so that there are no signal clashes and that complicated
strings of possibly many merged or biased images can be processed and outputted. The testing process will be
discussed where each layer is tested for k-value and extra operations which are then compared to MATLAB test
images from the Image Processing Toolbox or hand written m-files as a basis for comparison. The paper will
also include how certain areas have been made more efficient to make the system faster and to reduce space on
the FPGA by reducing the number of convolution kernels compared to the latter.
This paper shows research into the development of techniques that can be used to recover what was written
on a paper document after attempts have been made to obscure the content via methods such as burning or
bleach for example. Here instead of using expensive high-tech imagery and infrared equipment, there is the aim
of using off-the-shelf equipment to reduce economic costs in the form of a Sony Ericsson Mobile Phone with
a 2.0 mega pixel camera with built in light. The latter was used in the data collection phase after the test
documents were produced, various factors were considered here such as light reflection and incident angles on
the paper, position of camera, light frequencies, visible light collection and night mode light collection in order to
achieve the optimum test image. The FPGA was then brought in for the post-collection processing of the images
using techniques currently developed using graphical block methodologies for ease of use, then the best string
of operations to obtain the most efficient results of what was previously written will be presented by comparing
it to a similar untouched document. The paper then explains the expansions to the experiments which include
different types and coloured inks from various sources which include standard pens to inkjet printer cartridges
on numerously coloured paper to see how truly effect the developed technique is.
Presented in this paper is the design of a skin filter which unlike many systems already developed for use, this
system will not use RGB or HSI colour but an 8-bit greyscale instead. This is done in order to make the
system more convenient to employ on an FPGA, to increase the speed to better enable real-time imaging and
to make it easier to combine with the previously designed binary based algorithms. This paper will discuss the
many approaches and methods that could be considered such as Bayes format and thresholds, pixel extraction,
mathematical morphological strings, edge detection or a combination of the previous and a discussion about
which provided the best performance. The research for this skin filter was carried out in two stages, firstly on
people who had an ethnic origin of White - British, Asian or Asian British, Chinese and Mixed White and Asian.
The second phase which won't be included here in great detail will cover the same principles for the other ethnic
backgrounds of Black or Black British - Caribbean or Africa, Other Black background, Asian or Asian British
- Indian, Pakistani or Bangladeshi. This is due to the fact that we have to modify the parameters that govern
the detection process to account for greyscale changes in the skin tone, texture and intensity; however the same
principles would still be applied for general detection and integration into the previous algorithm. The latter is
discussed and what benefits it will give.
KEYWORDS: Field programmable gate arrays, Binary data, Light sources and illumination, Image processing, Digital signal processing, Cameras, Imaging systems, Information security, Clocks, Signal detection
In this paper, there is an investigation into the possibility of executing a Morphological Scene Change Detection
(MSCD) system on a Field Programmable Gate Array (FPGA), which would allow its set up in virtually any
location, with its purpose to detect intruders and raise an alarm to call security personal, and a signal to initial
a lockdown of the local area. This paper will include how the system was scaled down from the full building
multi-computer system, to an FPGA without losing any functionality using Altera's DSP Builder development
tool. Also included is the analysis of the different situations which the system would encounter in the field,
and their respective alarm triggering levels, these include indoors, outdoors, close-up, distance, high-brightness,
low-light, bad weather, etc. The triggering mechanism is a pixel counter and threshold system, and its adaptive
design will be included. All the results shown in this paper, will also be verified by MATLAB m-files running on
a full desktop PC, to show that the results obtained from the FPGA based system are accurate.
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