In this paper, is proposed a system that identifies the location and dimensions of the characters
relative to the image of a vehicular plate, when the location of the plate has not been accurate. The system is
divided into 4 stages, each with a specific purpose. Which are: binarization by thresholding, morphological
filtering, identification of the largest area and segmentation similarity. The first stage is used to find at the extent
if possible, the region occupied by the plate relative to the rest of the image. Then, in the filtering step, it seeks
to eliminate as far as possible the noise that interferes with the identification of the characters. The third stage is
used to identify the region occupied by the plate. Finally, in the fourth and last stage the segmentation by
similarity is used to identify position and dimension of the characters in the image, in stage a Kohonen neural
network is used.
A STUDY AND ANALYSIS OF DIFFERENT EDGE DETECTION TECHNIQUEScscpconf
In the first study [1], a combination of K-means, watershed segmentation method, and Difference In Strength (DIS) map were used to perform image segmentation and edge detection
tasks. We obtained an initial segmentation based on K-means clustering technique. Starting from this, we used two techniques; the first is watershed technique with new merging
procedures based on mean intensity value to segment the image regions and to detect their boundaries. The second is edge strength technique to obtain accurate edge maps of our images without using watershed method. In this technique: We solved the problem of undesirable over segmentation results produced by the watershed algorithm, when used directly with raw data images. Also, the edge maps we obtained have no broken lines on entire image. In the 2nd study level set methods are used for the implementation of curve/interface evolution under various forces. In the third study the main idea is to detect regions (objects) boundaries, to isolate and extract individual components from a medical image. This is done using an active contours to detect regions in a given image, based on techniques of curve evolution, Mumford–Shah functional for segmentation and level sets. Once we classified our images into different intensity regions based on Markov Random Field. Then we detect regions whose boundaries are not necessarily defined by gradient by minimize an energy of Mumford–Shah functional forsegmentation, where in the level set formulation, the problem becomes a mean-curvature which will stop on the desired boundary. The stopping term does not depend on the gradient of the image as in the classical active contour. The initial curve of level set can be anywhere in the image, and interior contours are automatically detected. The final image segmentation is one
closed boundary per actual region in the image.
A STUDY AND ANALYSIS OF DIFFERENT EDGE DETECTION TECHNIQUEScscpconf
In the first study [1], a combination of K-means, watershed segmentation method, and Difference In Strength (DIS) map were used to perform image segmentation and edge detection
tasks. We obtained an initial segmentation based on K-means clustering technique. Starting from this, we used two techniques; the first is watershed technique with new merging
procedures based on mean intensity value to segment the image regions and to detect their boundaries. The second is edge strength technique to obtain accurate edge maps of our images without using watershed method. In this technique: We solved the problem of undesirable over segmentation results produced by the watershed algorithm, when used directly with raw data images. Also, the edge maps we obtained have no broken lines on entire image. In the 2nd study level set methods are used for the implementation of curve/interface evolution under various forces. In the third study the main idea is to detect regions (objects) boundaries, to isolate and extract individual components from a medical image. This is done using an active contours to detect regions in a given image, based on techniques of curve evolution, Mumford–Shah functional for segmentation and level sets. Once we classified our images into different intensity regions based on Markov Random Field. Then we detect regions whose boundaries are not necessarily defined by gradient by minimize an energy of Mumford–Shah functional forsegmentation, where in the level set formulation, the problem becomes a mean-curvature which will stop on the desired boundary. The stopping term does not depend on the gradient of the image as in the classical active contour. The initial curve of level set can be anywhere in the image, and interior contours are automatically detected. The final image segmentation is one
closed boundary per actual region in the image.
FORGERY (COPY-MOVE) DETECTION IN DIGITAL IMAGES USING BLOCK METHODeditorijcres
AKHILESH KUMAR YADAV, DEENBANDHU SINGH, VIVEK KUMAR
Department of Computer Science and Engineering
Babu Banarasi Das University, Lucknow
akhi2232232@gmail.com, deenbandhusingh85@gmail.com, vivek.kumar0091@gmail.com
ABSTRACT- Digital images can be easily modified using powerful image editing software. Determining whether a manipulation is innocent of sharpening from those which are malicious, such as removing or adding parts to an image is the topic of this paper. In this paper we focus on detection of a special type of forgery-the Copy-Move forgery, in this part of the original image is copied moved to desired location in the same image and pasted. The proposed method compress images using DWT (discrete wavelet transform) and divided into blocks and choose blocks than perform feature vector calculation and lexicographical sorting and duplicated blocks are identified after sorting. This method is good at some manipulation/attack likes scaling, rotation, Gaussian noise, smoothing, JPEG compression etc.
INDEX TERMS- Copy-Move forgery, Wavelet Transform, Lexicographical Sorting, Region Duplication Detection.
Copy-Rotate-Move Forgery Detection Based on Spatial DomainSondosFadl
we propose a method which is efficient and fast for detecting Copy-Move regions even when the copied region was undergone rotation modify in spatial domain.
morphological tecnquies in image processingsoma saikiran
it describes you about different types of morphological techniques in image processing and what is the function and applications of morphological tecniques in image processing
At the end of this lecture, you should be able to;
describe the importance of morphological features in an image.
describe the operation of erosion, dilation, open and close operations.
identify the practical advantage of the morphological operations.
apply morphological operations for problem solving.
Image Interpolation Techniques with Optical and Digital Zoom Concepts -semina...mmjalbiaty
full details about Spatial and Intensity Resolution , optical and digital zoom concepts and the common three interpolation algorithms for implementing zoom in image processing
IMAGE ENCRYPTION BASED ON DIFFUSION AND MULTIPLE CHAOTIC MAPSIJNSA Journal
In the recent world, security is a prime important issue, and encryption is one of the best alternative way to ensure security. More over, there are many image encryption schemes have been proposed, each one of them has its own strength and weakness. This paper presents a new algorithm for the image encryption/decryption scheme. This paper is devoted to provide a secured image encryption technique using multiple chaotic based circular mapping. In this paper, first, a pair of sub keys is given by using chaotic logistic maps. Second, the image is encrypted using logistic map sub key and in its transformation leads to diffusion process. Third, sub keys are generated by four different chaotic maps. Based on the initial conditions, each map may produce various random numbers from various orbits of the maps.
Among those random numbers, a particular number and from a particular orbit are selected as a key for the encryption algorithm. Based on the key, a binary sequence is generated to control the encryption algorithm. The input image of 2-D is transformed into a 1- D array by using two different scanning pattern (raster and Zigzag ) and then divided into various sub blocks. Then the position permutation and value permutation is applied to each binary matrix based on multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the encrypted images. The salient features of the proposed image encryption method are loss-less, good peak signal –to noise ratio (PSNR), Symmetric key encryption, less cross correlation, very large number of secret keys, and key-dependent pixel value replacement.
Texture mapping is a method for defining high frequency detail, surface texture, or color information on a computer-generated graphic or 3D model. Its application to 3D graphics was pioneered by Edwin Catmull in 1974.
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license plate. The system is implemented on the entrance for security control of a highly restricted area like
military zones or area around top government offices e.g.Parliament, Supreme Court etc.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
FORGERY (COPY-MOVE) DETECTION IN DIGITAL IMAGES USING BLOCK METHODeditorijcres
AKHILESH KUMAR YADAV, DEENBANDHU SINGH, VIVEK KUMAR
Department of Computer Science and Engineering
Babu Banarasi Das University, Lucknow
akhi2232232@gmail.com, deenbandhusingh85@gmail.com, vivek.kumar0091@gmail.com
ABSTRACT- Digital images can be easily modified using powerful image editing software. Determining whether a manipulation is innocent of sharpening from those which are malicious, such as removing or adding parts to an image is the topic of this paper. In this paper we focus on detection of a special type of forgery-the Copy-Move forgery, in this part of the original image is copied moved to desired location in the same image and pasted. The proposed method compress images using DWT (discrete wavelet transform) and divided into blocks and choose blocks than perform feature vector calculation and lexicographical sorting and duplicated blocks are identified after sorting. This method is good at some manipulation/attack likes scaling, rotation, Gaussian noise, smoothing, JPEG compression etc.
INDEX TERMS- Copy-Move forgery, Wavelet Transform, Lexicographical Sorting, Region Duplication Detection.
Copy-Rotate-Move Forgery Detection Based on Spatial DomainSondosFadl
we propose a method which is efficient and fast for detecting Copy-Move regions even when the copied region was undergone rotation modify in spatial domain.
morphological tecnquies in image processingsoma saikiran
it describes you about different types of morphological techniques in image processing and what is the function and applications of morphological tecniques in image processing
At the end of this lecture, you should be able to;
describe the importance of morphological features in an image.
describe the operation of erosion, dilation, open and close operations.
identify the practical advantage of the morphological operations.
apply morphological operations for problem solving.
Image Interpolation Techniques with Optical and Digital Zoom Concepts -semina...mmjalbiaty
full details about Spatial and Intensity Resolution , optical and digital zoom concepts and the common three interpolation algorithms for implementing zoom in image processing
IMAGE ENCRYPTION BASED ON DIFFUSION AND MULTIPLE CHAOTIC MAPSIJNSA Journal
In the recent world, security is a prime important issue, and encryption is one of the best alternative way to ensure security. More over, there are many image encryption schemes have been proposed, each one of them has its own strength and weakness. This paper presents a new algorithm for the image encryption/decryption scheme. This paper is devoted to provide a secured image encryption technique using multiple chaotic based circular mapping. In this paper, first, a pair of sub keys is given by using chaotic logistic maps. Second, the image is encrypted using logistic map sub key and in its transformation leads to diffusion process. Third, sub keys are generated by four different chaotic maps. Based on the initial conditions, each map may produce various random numbers from various orbits of the maps.
Among those random numbers, a particular number and from a particular orbit are selected as a key for the encryption algorithm. Based on the key, a binary sequence is generated to control the encryption algorithm. The input image of 2-D is transformed into a 1- D array by using two different scanning pattern (raster and Zigzag ) and then divided into various sub blocks. Then the position permutation and value permutation is applied to each binary matrix based on multiple chaos maps. Finally the receiver uses the same sub keys to decrypt the encrypted images. The salient features of the proposed image encryption method are loss-less, good peak signal –to noise ratio (PSNR), Symmetric key encryption, less cross correlation, very large number of secret keys, and key-dependent pixel value replacement.
Texture mapping is a method for defining high frequency detail, surface texture, or color information on a computer-generated graphic or 3D model. Its application to 3D graphics was pioneered by Edwin Catmull in 1974.
AUTOMATIC LICENSE PLATE RECOGNITION SYSTEM FOR INDIAN VEHICLE IDENTIFICATION ...Kuntal Bhowmick
Automatic License Plate Recognition (ANPR) is a practical application of image processing which uses number (license) plate is used to identify the vehicle. The aim is to design an efficient automatic vehicle identification system by using the
vehicle license plate. The system is implemented on the entrance for security control of a highly restricted area like
military zones or area around top government offices e.g.Parliament, Supreme Court etc.
It is worth mentioning that there is a scarcity in researches that introduce an automatic number plate recognition for indian vechicles.In this paper, a new algorithm is presented for Indian vehicle’s number plate recognition system. The proposed algorithm consists of two major parts: plate region extraction and plate recognition.Vehicle number plate region is extracted using the image segmentation in a vechicle image.Optical character recognition technique is used for the character recognition. And finally the resulting data is used to compare with the records on a database so as to come up with the specific information like the vehicle’s owner, registration state, address, etc.
The performance of the proposed algorithm has been tested on real license plate images of indian vechicles. Based on the experimental results, we noted that our algorithm shows superior performance special in number plate recognition phase.
Hybrid Technique for Copy-Move Forgery Detection Using L*A*B* Color Space IJEEE
Copy-move forgery is applied on an image to hide a region or an object. Most of the detection techniques either use transform domain or spatial domain information to detect the forgery. This paper presents a hybrid method to detect the forgery making use of both the domains i.e. transform domain in whichSVD is used to extract the useful information from image and spatial domain in which L*a*b* color space is used. Here block based approach and lexicographical sorting is used to group matching feature vectors. Obtained experimental results demonstrate that proposed method efficiently detects copy-move forgery even when post-processing operations like blurring, noise contamination, and severe lossy compression are applied.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The development of multimedia system technology in Content based Image Retrieval (CBIR) System is
one in every of the outstanding area to retrieve the images from an oversized collection of database. The feature
vectors of the query image are compared with feature vectors of the database images to get matching images.It is
much observed that anyone algorithm isn't beneficial in extracting all differing kinds of natural images. Thus an
intensive analysis of certain color, texture and shape extraction techniques are allotted to spot an efficient CBIR
technique that suits for a selected sort of images. The Extraction of an image includes feature description and
feature extraction. During this paper, we tend to projected Color Layout Descriptor (CLD), grey Level Co-
Occurrences Matrix (GLCM), Marker-Controlled Watershed Segmentation feature extraction technique that
extract the matching image based on the similarity of Color, Texture and shape within the database. For
performance analysis, the image retrieval timing results of the projected technique is calculated and compared
with every of the individual feature.
FUZZY SET THEORETIC APPROACH TO IMAGE THRESHOLDINGIJCSEA Journal
Thresholding is a fast, popular and computationally inexpensive segmentation technique that is always critical and decisive in some image processing applications. The result of image thresholding is not always satisfactory because of the presence of noise and vagueness and ambiguity among the classes. Since the theory of fuzzy sets is a generalization of the classical set theory, it has greater flexibility to capture faithfully the various aspects of incompleteness or imperfectness in information of situation. To overcome this problem, in this paper we proposed a two-stage fuzzy set theoretic approach to image thresholding utilizing the measure of fuzziness to evaluate the fuzziness of an image and to determine an adequate threshold value. At first, images are preprocessed to reduce noise without any loss of image details by fuzzy rule-based filtering and then in the final stage a suitable threshold is determined with the help of a fuzziness measure as a criterion function. Experimental results on test images have demonstrated the effectiveness of this method.
Color Image Watermarking Application for ERTU CloudCSCJournals
Color image is one of the the Egyptian Radio and Television Union (ERTU)’s content should be saved from any abuse from outside or inside the organization alike. The application of saving color image deploys the watermarking techniques based on Discrete Wavelet Transform (DWT). This application is implemented by software that suits the ERTU’s cloud besides many tests to insure the originality of the photo and if there is any changes applied on. All that provides the essential objectives of the cloud to overcome the limitation of distance as well as provide reliable and trusted services to Authorized group.
OTSU Thresholding Method for Flower Image Segmentationijceronline
Segmentation is basic process in image processing. It always produces an effective result for next process. In this paper, we proposed the flower image segmentation. Oxford flower collection is used for segmentation.Different segmentation techniques are available. Different techniques and algorithm are developed to describe the segmentation.We proposed a OTSU thresholding technique for flower image segmentation in this paper. which gives good result as compared with the other methods and simple also.Segmentation subdivide the image into different parts.firstly, segmentation techniques and then otsu thresholding method described in this paper.CIE L*a*b color space is used in thresholding for better results.Thresholding apply seperatly on each L, a and b component. accordingly the features can be extracted like shape, color, texture etc. finally, results with the flower images are shown.
Chaos Image Encryption using Pixel shuffling cscpconf
The advent of wireless communications, both inside and outside the home-office environment
has led to an increased demand for effective encryption systems. The beauty of encryption
technology comes out in more pronounced way when there is no absolute relation between
cipher and original data and it is possible to rebuild the original image in much easier way. As
chaotic systems are known to be more random and non-predictable, they can be made utilized in
achieving the encryption. The transposition technology of encryption systems requires scrambleness
behaviour in order to achieve the encryption of the data. This scrambleness behaviour can
be derived from the randomness property of chaos which can be better utilized in the techniques
like transposition system. In wireless communication systems, bandwidth utilization is an important
criterion. In order to use encryption system in wireless communication; key space plays an
important role for the efficient utilization of the bandwidth. In this paper we present a chaosbased
encryption algorithm for images. This algorithm is based on pixel scrambling where in the
randomness of the chaos is made utilized to scramble the position of the data. The position of the
data is scrambled in the order of randomness of the elements obtained from the chaotic map and
again rearranged back to their original position in decryption process. The same algoritm is
tested with two different maps and performance analysis is done to select best suited map for encription.
DOMAIN SPECIFIC CBIR FOR HIGHLY TEXTURED IMAGEScseij
It is A Challenging Task To Build A Cbir System Which Primarily Works On Texture Values As There
Meaning And Semantics Needs A Special Care To Be Mapped With Human Based Languages. We Have
Consider Highly Textured Images Having Properties(Entropy, Homogeneity, Contrast, Cluster Shade, Auto
Correlation)And Have Mapped Using A Fuzzy Minmax Scale W.R.T. Their Degree(High, Low,
Medium)And Technical Interpetation.This Developed System Is Performing Well In Terms Of Precision
And Recall Value Showing That Semantic Gap Has Been Reduced For Highly Textured Images Based Cbir.
IMAGE RESTORATION BASED ON MORPHOLOGICAL OPERATIONSijcseit
Image processing including noise suppression, feature extraction, edge detection, image segmentation,
shape recognition, texture analysis, image restoration and reconstruction, image compression etc uses
mathematical morphology which is a method of nonlinear filters.
It is modulated from traditional morphology to order morphology, soft mathematical morphology and fuzzy
soft mathematical morphology. This paper is covers 6 morphological operations which are implemented in
the matlab program, including erosion, dilation, opening, closing, boundary extraction and region filling.
Image restoration based on morphological operationsijcseit
Image processing including noise suppression, feature extraction, edge detection, image segmentation,
shape recognition, texture analysis, image restoration and reconstruction, image compression etc uses
mathematical morphology which is a method of nonlinear filters.
It is modulated from traditional morphology to order morphology, soft mathematical morphology and fuzzy
soft mathematical morphology. This paper is covers 6 morphological operations which are implemented in
the matlab program, including erosion, dilation, opening, closing, boundary extraction and region filling.
Color Particle Filter Tracking using Frame Segmentation based on JND Color an...IOSRJVSP
Object tracking is one of the most important components in numerous applications of computer vision. Color can provide an efficient visual feature for tracking non-rigid objects in real-time. The color is chosen as tracking feature to make the process scale and rotation invariant. The color of an object can vary over time due to variations in the illumination conditions, the visual angle and the camera parameters. This paper presents the integration of color distributions into particle filtering. The color feature is extracted using our novel 4D color histogram of the image, which is determined using JND color similarity threshold and connectivity of the neighboring pixels. Particle filter tracks several hypotheses simultaneously and weighs them according to their similarity to the target model. The popular Bhattacharyya coefficient is used as similarity measure between two color distributions. The tracking results are compared on the basis of precision over the data set of video sequences from the website http://visualtracking.net of CVPR13 bench marking paper. The proposed tracker yields better precision values as compared to previous reported results
AUTOMATIC THRESHOLDING TECHNIQUES FOR OPTICAL IMAGESsipij
Image segmentation is one of the important tasks in computer vision and image processing. Thresholding is
a simple but most effective technique in segmentation. It based on classify image pixels into object and
background depended on the relation between the gray level value of the pixels and the threshold. Otsu
technique is a robust and fast thresholding techniques for most real world images with regard to uniformity
and shape measures. Otsu technique splits the object from the background by increasing the separability
factor between the classes. Our aim form this work is (1) making a comparison among five thresholding
techniques (Otsu technique, valley emphasis technique, neighborhood valley emphasis technique, variance
and intensity contrast technique, and variance discrepancy technique)on different applications. (2)
determining the best thresholding technique that extracted the object from the background. Our
experimental results ensure that every thresholding technique has shown a superior level of performance
on specific type of bimodal images.
PERFORMANCE EVALUATION OF DIFFERENT TECHNIQUES FOR TEXTURE CLASSIFICATION cscpconf
Texture is the term used to characterize the surface of a given object or phenomenon and is an
important feature used in image processing and pattern recognition. Our aim is to compare
various Texture analyzing methods and compare the results based on time complexity and
accuracy of classification. The project describes texture classification using Wavelet Transform
and Co occurrence Matrix. Comparison of features of a sample texture with database of
different textures is performed. In wavelet transform we use the Haar, Symlets and Daubechies
wavelets. We find that, thee ‘Haar’ wavelet proves to be the most efficient method in terms of
performance assessment parameters mentioned above. Comparison of Haar wavelet and Cooccurrence
matrix method of classification also goes in the favor of Haar. Though the time
requirement is high in the later method, it gives excellent results for classification accuracy
except if the image is rotated.
Similar to Identification system of characters in vehicular plates (20)
Exploratory study on the use of crushed cockle shell as partial sand replacem...IJRES Journal
The increasing demand for natural river sand supply for the use in construction industry along
with the issue of environmental problem posed by the dumping of cockle shell, a by-product from cockle
business have initiated research towards producing a more environmental friendly concrete. This research
explores the potential use of cockle shell as partial sand replacement in concrete production. Cockle shell used
in this experimental work were crushed to smaller size almost similar to sand before mixed in concrete. A total
of six concrete mixtures were prepared with varying the percentages of cockle shell viz. 0%, 5%, 10%, 15%,
20% and 25%. All the specimens were subjected to continuous water curing. The compressive strength test was
conducted at 28 days in accordance to BS EN 12390. Finding shows that integration of suitable content of
crushed cockle shell of 10% as partial sand replacement able to enhance the compressive strength of concrete.
Adopting crushed cockle shell as partial sand replacement in concrete would reduce natural river sand
consumption as well as reducing the amount of cockle shell disposed as waste.
Congenital Malaria: Correlation of Umbilical Cord Plasmodium falciparum Paras...IJRES Journal
The vertical (trans-placental) transmission of the parasite Plasmodium falciparum from
pregnant mother to fetus during gestational period was investigated in a clinical research involving 43 full term
pregnant women in selected Hospitals in Jimeta Yola, Adamawa State Nigeria. During the observational study,
parasitemia was determined by light microscopic examination of umbilical and maternal peripheral blood film
for the presence of the trophozoites of Plasmodium falciparum. Correlational analysis was then carried on the
result obtained at p<0.05.><0.05) was established between maternal peripheral blood and umbilical cord
blood parasitemia with Pearson’s correlation coefficient of 0.762. Thus, in a malaria endemic area like Yola,
Adamawa State, Nigeria, with a stable transmission of parasite, there is a high probability of vertical
transmission of Plasmodium falciparum parasite from mother to fetus during gestation that can be followed by
the presentation of the symptoms of malaria by the newborn and other malaria related complications. Families
are advised to consistently sleep under appropriately treated insecticide mosquito net to avoid mosquito bite and
subsequent infestation.
Review: Nonlinear Techniques for Analysis of Heart Rate VariabilityIJRES Journal
Heart rate variability (HRV) is a measure of the balance between sympathetic mediators of heart
rate that is the effect of epinephrine and norepinephrine released from sympathetic nerve fibres acting on the
sino-atrial and atrio-ventricular nodes which increase the rate of cardiac contraction and facilitate conduction at
the atrio-ventricular node and parasympathetic mediators of heart rate that is the influence of acetylcholine
released by the parasympathetic nerve fibres acting on the sino-atrial and atrio-ventricular nodes leading to a
decrease in the heart rate and a slowing of conduction at the atrio-ventricular node. Sympathetic mediators
appear to exert their influence over longer time periods and are reflected in the low frequency power(LFP) of
the HRV spectrum (between 0.04Hz and 0.15 Hz).Vagal mediators exert their influence more quickly on the
heart and principally affect the high frequency power (HFP) of the HRV spectrum (between 0.15Hz and 0.4
Hz). Thus at any point in time the LFP:HFP ratio is a proxy for the sympatho- vagal balance. Thus HRV is a
valuable tool to investigate the sympathetic and parasympathetic function of the autonomic nervous system.
Study of HRV enhance our understanding of physiological phenomenon, the actions of medications and disease
mechanisms but large scale prospective studies are needed to determine the sensitivity, specificity and predictive
values of heart rate variability regarding death or morbidity in cardiac and non-cardiac patients. This paper
presents the linear and nonlinear to analysis the HRV.
Dynamic Modeling for Gas Phase Propylene Copolymerization in a Fluidized Bed ...IJRES Journal
A two-phase model is proposed for describing the dynamics of a fluidized bed reactor used for
polypropylene production. In the proposed model, the fluidized bed is divided into an emulsion and bubble
phase where the flow of gas is considered to be plug flow through the bubbles and perfectly mixed through the
emulsion phase. Similar previous models, consider the reaction in the emulsion phase only. In this work the
contribution of reaction in the bubble phase is considered and its effect on the overall polypropylene production
is investigated the kinetic model is combined with hydrodynamic model in order to develop a comprehensive
model for gas-phase propylene copolymerization reactor. Simulation profiles of the proposed model were
compared with those of well mixed model for the emulsion phase temperature. The simulated temperature
profile showed a lower rate of change compared to the previously reported models due to lower polymerization
rate. Model simulation showed that about 13% of the produced polymer comes from the bubble phase and this
considerable amount of polymerization in the bubbles should not be neglected in any modeling attempt.
Study and evaluation for different types of Sudanese crude oil propertiesIJRES Journal
Sudanese crude oil is regarded as one of the sweet types of crude in the world, Sulphur containing
compounds are un desirable in petroleum because they de activate the catalyst during the refining processes and
are the main source of acid rains and environmental pollution.(Mark Cullen 2001),Since it contains considerable
amount of salts and acids, it negatively impact the production facilities and transportation lines with corrosive
materials. However it suffers other problems in flow properties represented by the high viscosity and high
percentage of wax. Samples were collected after the initial and final treatment at CPF, and tested for
physical and chemical properties.wax content is in the range 23-31 weight % while asphalting content is about
0.1 weight% . Resin content is 13-7 weight % and deposits are 0.01 weight%. The carbon number distribution in
the crude is in the range 7-35 carbon atoms. The pour point vary between 39°C-42°C and the boiling point is in
the range 70 °C - 533 °C.
A Short Report on Different Wavelets and Their StructuresIJRES Journal
This article consists of basics of wavelet analysis required for understanding of and use of wavelet
theory. In this article we briefly discuss about HAAR wavelet transform their space and structures.
A Case Study on Academic Services Application Using Agile Methodology for Mob...IJRES Journal
Recently, Mobile Cloud Computing reveals many modern development areas in the Information
Technology industry. Several software engineering frameworks and methodologies have been developed to
provide solutions for deploying cloud computing resources on mobile application development. Agile
methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a
Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An
Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud
computing resources deployment. Also many related issues is discussed such as how software engineering
modern methodologies (advances) influenced the development process.
Wear Analysis on Cylindrical Cam with Flexible RodIJRES Journal
Firstly, the kinetic equation of spatial cylindrical cam with flexible rod has been established. Then, an
accurate cylindrical cam mechanism model has been established based on the spatial modeling software
Solidworks. The dynamic effect of flexible rod on mechanical system was studied in detail based on the
mechanical system dynamics analytical software Adams, and Archard wear model is used to predict the wear of
the cam. We used Ansys to create finite element model of the cam link, extracted the first five order mode to
export into Adams. The simulation results show that the dynamic characteristics of spatial cylindrical cam
mechanical system with flexible rod is closed to ideal mechanism. During the cam rotate one cycle, the collision
in the linkage with a clearance occurs in some special location, others still keep a continuous contact, and the
prediction of wear loss is smaller than rigid body.
DDOS Attacks-A Stealthy Way of Implementation and DetectionIJRES Journal
Cloud Computing is a new paradigm provides various host service [paas, saas, Iaas over the internet.
According to a self-service,on-demand and pay as you use business model,the customers will obtain the cloud
resources and services.It is a virtual shared service.Cloud Computing has three basic abstraction layers System
layer(Virtual Machine abstraction of a server),Platform layer(A virtualized operating system, database and
webserver of a server and Application layer(It includes Web Applications).Denial of Service attack is an attempt
to make a machine or network resource unavailable to the intended user. In DOS a user or organization is
deprived of the services of a resource they would normally expect to have.A Successful DOS attack is a highly
noticeable event impacting the entire online user base.DOS attack is found by First Mathematical Metrical
Method (Rate Controlling,Timing Window,Worst Case and Pattern Matching)DOS attack not only affect the
Quality of the service and also affect the performance of the server. DDOS attacks are launched from Botnet-A
large Cluster of Connected device(cellphone,pc or router) infected with malware that allow remote control by an
attacker. Intruder using SIPDAS in DDOS to perform attack.SIPDAS attack strategies are detected using Heap
Space Monitoring Algorithm.
An improved fading Kalman filter in the application of BDS dynamic positioningIJRES Journal
Aiming at the poor dynamic performance and low navigation precision of traditional fading
Kalman filter in BDS dynamic positioning, an improved fading Kalman filter based on fading factor vector is
proposed. The fading factor is extended to a fading factor vector, and each element of the vector corresponds to
each state component. Based on the difference between the actual observed quantity and the predicted one, the
value of the vector is changed automatically. The memory length of different channel is changed in real time
according to the dynamic property of the corresponding state component. The actual observation data of BDS is
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Identification system of characters in vehicular plates
1. International Journal of Research in Engineering and Science (IJRES)
ISSN (Online): 2320-9364, ISSN (Print): 2320-9356
www.ijres.org Volume 3 Issue 12 ǁ December. 2015 ǁ PP.41-52
www.ijres.org 41 | Page
Identification system of characters in vehicular plates
S. Garcia1
, C. Aquino2
, D. Samorano3
1
ESIME Culhuacan, National Polytechnic Institute.
2
ESIME Culhuacan, National Polytechnic Institute.
3
ESIME Culhuacan, National Polytechnic Institute.
Abstract: In this paper, is proposed a system that identifies the location and dimensions of the characters
relative to the image of a vehicular plate, when the location of the plate has not been accurate. The system is
divided into 4 stages, each with a specific purpose. Which are: binarization by thresholding, morphological
filtering, identification of the largest area and segmentation similarity. The first stage is used to find at the extent
if possible, the region occupied by the plate relative to the rest of the image. Then, in the filtering step, it seeks
to eliminate as far as possible the noise that interferes with the identification of the characters. The third stage is
used to identify the region occupied by the plate. Finally, in the fourth and last stage the segmentation by
similarity is used to identify position and dimension of the characters in the image, in stage a Kohonen neural
network is used.
Keywords: Kohonen, lqv, Otsu, morphological
I. Introduction
Nowadays technology has grown favorably and has developed new solutions and alternatives for the
improvement of society, although it is noteworthy that technology does not advance in the same way in all
countries either by lack of financial resources, lack of education and training or lack of initiative and sometimes
the lack of government support. In the case of Mexico optical character recognition has not been fully
investigated which is a very broad topic and of most importance for alphanumeric reading of any text or
vehicular plates. Some previous papers are cited in [1] - [2].
II. Binarization
To emphasize at the possible extent the region that occupies the plate with the rest of the image the
binarization technique was used. Binarization is an image processing technique that consists of the reduction of
a digital image information with L + 1 levels of gray, where 0L 255, at two values: 0 (black) and 255 (white).
The process is very simple, and involves comparing each pixel of the image with a determined threshold which
is the limit value that determines whether a pixel would be black or white in color. The values of the image that
are larger than the threshold take a value of the 255 for white and the other pixels take the value 0 for black.
2.1. Thresholding
In order to obtain the threshold, the Otsu's thresholding method was used to determine the optimum
threshold topt, by maximizing a parameter that Otsu defined as the variance between classes, and is given by
equation (1).
σB
2
= ω1 μ1
− μT
2
+ ω2 μ2
− μT
2
(1)
where,
𝜇1 =
𝑘∙𝑝 𝑘
𝜔1
𝑡
𝑘=1 , is the mean of class 1
𝜇2 =
𝑘∙𝑝 𝑘
𝜔2
𝐿
𝑘=1+1 , is the mean of class 2
𝜇 𝑇 = 𝑘 ∙ 𝑝 𝑘
𝐿
𝑘=1 , is the mean of the distribution (image)
The parameters 1 y 2 represent the sum of probabilities pk=fk/N, where fkis the frequency in which appears
level of intensity k with 0kL and N the number of pixels in the image, from 0 up to t and t + 1 to L
respectively. That is,
𝜔1 = 𝑝 𝑘
𝑡
𝑘=0 y 𝜔2 = 𝑝 𝑘
𝐿
𝑘=𝑡+1
2. Identification system of characters in vehicular plates
www.ijres.org 42 | Page
To determine the optimal threshold topt, an iterative process is followed, that starts at t = 1 and ends at t = L-1
since if t = 0 or L would only exist a class (class 1 or class 2).Thus, after performing the calculations of the
variance between classes 𝜎 𝐵
2
for each t, the optimal threshold is obtained topt when𝜎 𝐵
2
reaches its maximum value.
In example, consider the digital image with 8 levels of grey shown in Figure 1.
Figure 1. Digital image with 8 levels of gray (right). The matrix on the left represents the level of intensity of
each pixel.
In table 1the values obtained from the variance between classes are shown when applying (1) for each
candidate t.The maximum is obtained when t = 2. In this way, the pixels with intensity values greater than 2 are
placed in Class 2 (intensity level 255) and the rest in class 1 (intensity level 1) as shown in Figure 2.
Table 1. Variance between classes for each candidate t value of the image in Figure 1.
t 1 2 3 4 5 6
𝝈 𝑩
𝟐 4.95 5.33 3.71 5.14 3.06 1.75
Figure 2. The binarized image (right) with t=2 of the image in figure 1. At the left the associated matrix is
shown.
In Figure 3, the binarization of the digital image of a plate with 256 levels of grey is shown. In the process
the Matlab graythresh in structions and im2bw were employed. The graythresh function determines the
optimal threshold topt and im2bw function performs the image binarization.
3. Identification system of characters in vehicular plates
www.ijres.org 43 | Page
Figure 3. Gray scale image (left). Binarized image (right).
Sometimes it is not possible to differentiate the region occupied by the plate with the rest of the image. In
Figure 4, it is observed how after the binarization, the region occupied by the plate is indistinguishable from the
rest of the image, because the vehicle is white color.
Figure 4. After binarization, it is not possible to differentiate the region occupied by the plate from the rest of
the image.
III. Morphological Filtering
Mathematical morphology is a widely used tool in image processing. The morphological operations may
simplify the image data, preserving the essential characteristics and eliminating irrelevant aspects. In this work it
is used after the binarization step, with the purpose to eliminate the weak connectivity dark areas within the
plate and which overlap to the region occupied by the characters.
4. Identification system of characters in vehicular plates
www.ijres.org 44 | Page
3.1 binary image
A binary image can be seen as a mapping set of Z2
Z2, where Z2
=ZZ with Z the integer set and Z2={0,1}.
Consider the binary matrix in Figure 5 that represents a binary image. In the figure is stated the origin of the
coordinates as well as the positive directions of the axes m,nZ. Each position (m, n) is mapped to a value of
the set Z2. Call this function X (m, n) the binary image that associates each position (pixel) a 0 or a 1. For
example X (1,1) = 0.
Figure 5. Binary matrix that represents a binary image.
3.2. Estructural element
The structural element B is a binary matrix with much smaller dimension than the image, which defines the
shape and size of the pixel's neighborhood that would be analyzed. The transposed of the structural element B,
denoted by B, is defined as the reflection on the origin of each item of B, ie, B = −B. In figure 6 a rectangular
structural element and its transposed are shown, the origin of the coordinates is marked with an underscore.
Figure 6. Structural element B with rectangular form (left) and it’s transposedB (right).
3.3. Dilation and erosion
Dilation and erosion are the two basic morphological operations. Dilation of a binary image X by the
structural element B, can be described as follows:
Step 1. A pixel (m, n) of X is selected to be analyzed.
Step 2. The origin ofB, is positioned at (m,n).
Step 3. The value of the pixel (m, n) is changed to the maximum value of the pixel's neighborhood defined by B.
On the other hand, the erosion of a binary image X by the structural element B is described as follows:
Step 1. A pixel (m, n) of X is selected to be analyzed.
Step 2. The origin of the transposed of B,is positioned, that is, B in (m,n).
Step 3. The value of the pixel (m, n) is changed to the minimum value of the pixel's neighborhood defined by B.
In Figures 7 and 8 is shown the effect of a dilation followed by an erosion over the binary matrix of Figure
5 by the structural element of Figure 6.
5. Identification system of characters in vehicular plates
www.ijres.org 45 | Page
Figure 7. Dilation operation. Input matrix (left), output matrix (right).
Figure 8. Erosion operation. Input matrix (left), output matrix (right).
Is observed how the effect of the dilation is to disconnect 0's regions with low continuity. Then, with the
erosion, 0's region strongly connected and that suffered a slight disconnect with dilation operation is
reconnected and returns to its original state. The combination of these operations and at this order is called
closing operation. Ideally, this is what you would expect| to happen with the plate characters. However, in real
conditions it is expected that most of the dark regions that overlaps and interfere with the plate would disappear,
so as to allow proper identification of the characters in the following process stages.
A square structural element of size 5 was used in this study, so that the effect of dilation wouldn’t be so
agresive as to disconnect the characters. To implement the closing operation, the Matlab's imclose instruction
was used. In Figure 9, two cases are shown where the operation gives good results and a third case in which the
6. Identification system of characters in vehicular plates
www.ijres.org 46 | Page
result is not so satisfactory, due that the interference region is strongly connected. An alternative to this case
would be to decrease the binarization threshold before filtering.
7. Identification system of characters in vehicular plates
www.ijres.org 47 | Page
Figure 9. Filtering over plates containing regions that interfere with characters
IV. Identification of the larger area
In stage 3 of the work, an identification of "the larger area" within the image is made, for the purpose of
getting closer to the region occupied by the plate. For this, the Matlab's function regionprops was used. This
function allows identifying connected components within the image, to later obtain basic properties of each
component such as: the area, perimeter, centroid, just to name a few.
8. Identification system of characters in vehicular plates
www.ijres.org 48 | Page
When the regionprops function is directly applied to a binary image, implicitly uses the
functionbwconncomp, this function identifies connected components and that generates a data structure that
provides among other things, the number of components and the location of the corresponding pixels to each
component.
Then, a very general description of a procedure is given that determines the connected components, that is
not necessarily the one followed by the bwconncomp function.
STEP 1. A pixel P with 1 as a value is selected and stored in the LP list.
STEP 2. A neighborhood of rectangular shape centered in P is generated, by default square shaped of dimension
3. In this case it is said that the window is of connectivity 8 (number of neighbors of P).
STEP 3. If there are neighbors of P with value of 1, these belong to the same component and are stored then in
the LP list.
In figure 10, the implementation of the bwconncomp function is shown, followed by the labelmatrix
function to a binary matrix, the labelmatrix function assigns a different label to each of the lists previously
obtained by the bwconncomp function. At the time of implementing a default 8 connectivity is used.
Figure 10. Identification of connected components. The original matrix (left) and the matrix with labels (right)
To identify the "larger area" within the image, the maximum of the "Areas" was obtained of the connected
components obtained by applying the regionprops function and using the "Area" property, that as such does
not correspond to the geometric definition. This property provides the number of pixels with value 1 of the
component.
After identifying the "larger area", is proceeded to identify the rectangle of least dimension that contains
that area. For this, the property BouningBox of the function regionprops was used, which gives the position of
the upper left corner (origin) as well as the length and width of the rectangle of least dimension that contains
that connected component. For example, the component 2 of figure 10 has it origin at position (1,5), length and
width of 3.
Under ideall conditions, one would expect that the component of greater area would be the plate, because it
is a connected component with most of its pixels with value of 1. However, unwanted scenarios may occur, for
example, that the plate be a connected subcomponent (the plate doesn’t have a frame and the car is light in
color) or that connected component exists with a larger area ( the plate having a frame and the car is light in
color).
In Figure 11 two cases are shown, the first close to the ideal, and at the second, the plate doesn’t have a
frame and the car is light in color.
9. Identification system of characters in vehicular plates
www.ijres.org 49 | Page
Figure 11. Obtaining the larger area.
V. Identification of characters
To identify the region occupied by the characters, the negative of the image obtained in the previous stage
was used. The negative of a binary image, consists in changing the pixels 1 to 0 and vice versa. Afterwards the
rectangle of least dimension containing each connected component is obtained. The length and width of each
rectangle were used as training patterns of a Kohonen neural network.
5.1. Kohonen neural network
There are two variants of the model, called LVQ (Learning Vector Quantization) one-dimensional and
SOM (Self Organization Map) usually two-dimensional but could even be three-dimensional. The LQV variant
was used in this work.
5.1.1. Architecture LQV
The original version (LVQ) consists of two layers, with N input neurons and M output neurons. Each of the
N input neurons are connected to the M output neurons through forward connections (feedforward), as
illustrated in Figure 12.
10. Identification system of characters in vehicular plates
www.ijres.org 50 | Page
Figure 12. LQV Architecture
Operation
1. The synaptic weights Wj are initialized with default or random values for every j=1,…,M, where;
Wj = [W1j, W2j, ⋯ , WNj ] (2)
2. For every t = 1,…,T and for every k=1,…P, where T is the number of epochs and P is number of training
patterns. Steps 3 and 4 are realized.
3. The input pattern Ek
is presented to the net, where;
Ek
= [E1
k
, E2
k
, ⋯ , EN
k
] (3)
and the euclidean distance is calculated for every j=1,..,M, that is:
dkj = Ek
− Wj (4)
4. The winner neuron j* is the one that has the least euclidan distance. Then, the weight Wj* is updated,
following the learning rule in (4), while the rest of the weights are maintained without change.
Wj∗ = Wj∗ + β(t) Ek
− Wj∗ (5)
where the parameter (t) is denominated as a learning parameter and is a bounded value between 0 and 1 that
decreases with t. The next expression may be used:
β(t) =
1
𝑡
(6)
In this work the number of input neurons is N=2, since the input patterns are defined like points in the
plane Ek
=[wk
, hk
], where wk
, hk
represent the width and length respectively of the container rectangle of the
connected component k. Besides, the dimensions wk
, hk
were normalized respect to the maximum width and
length respectively, that is:
𝑤 𝑘 =
𝑤 𝑘
𝑤 𝑚𝑎𝑥
ℎ 𝑘 =
ℎ 𝑘
ℎ 𝑚𝑎𝑥
(7)
On the other hand, the number of neurons in output core is M=4. In figure 13 the prefixed default values are
indicated with the ones that initialized the synaptic weights. At ideal conditions, it would be expected that in the
map would be defined the 4 zones that are indicated in figure 13. The zone 4 is the zone that has less probability
to classify the characters, due that this zone classifies components with proportion w/h > 1, andthe characters
maintain a proportion w/h <1. However, this zone is necessary to classify and to discard these type of
components. In any of the other zones, the characters can be classified.
11. Identification system of characters in vehicular plates
www.ijres.org 51 | Page
Figure 13. Initialization of weights and ideal zones of classification
In Figure 14, three cases are exhibited, where the zone is indicated where the characters were classified.
Figure 14. Classification zones of the characters.
VI. Conclusions
This paper presents a method for identifying the position, length and width of the rectangle of least
dimension that contains the characters in an image taken from a vehicular plate, when the plate's location has not
been accurate. It should be mentioned that from the identification in some cases is not possible to realize the
extraction, since it should be applied to a geometric correction, plus it is also possible that still exists noise in the
region occupied by some characters. However, the objective is not to have a prior stage to the extraction, instead
12. Identification system of characters in vehicular plates
www.ijres.org 52 | Page
useful information for the identification of the region occupied by the characters in the image and necessary
geometric correction.
References
[1] Andrade Miranda Gustavo, López Encalada José y Chávez Burbano Patricia,Vehicle control system using optical character
recognition, http://www.dspace.espol.edu.ec/bitstream/123456789/1458/1/2973 .pdf,
[2] Richard Gutiérrez, Ma. Fernanda Frydson y Phd. Boris Vintimilla, Application of computer vision for automatic recognition of
vehicular plates using conventional OCR's www.dspace.espol.edu.ec/.../Paper _Gutierrez_Frydson_Vintimilla.pdf
[3] Angulo Jesús, Segmentación de imágenes http://cmm.ensmp.fr/~angulo/publicat/AnguloSerra_CyS_ 05.pdf
[4] Duarte Domingo, Image segmentation using its histogram http://www.unne.edu.ar/unnevieja/Web/cyt/cyt/2001/7-
Tecnologicas/T-084.pdf
[5] Cáceres Tello Jesús, Artificial vision and morphological operations in binary images, http://www2.uah.es/jcaceres/uploaded/
articulos/FormatoVisonArtificial.pdf,
[6] National University of Quilmes http://iaci.unq.edu.ar/materias/vision/archivos/apuntes/Operaciones%20Morfol%C3%
B3gicas%20en%20Im%C3%A1genes%20Binarias%20-%20parte%203.pdf
[7] The Kohonen model,http://thales.cica.es/rd/Recursos/rd98/TecInfo/07/capitulo6.html,
[8] www.mathworks.com/help/images/ref/
AUTHOR PROFILE:
Silvestre Ascención García Sánchez. Born in Mexico DF on Jul 11, 1975, holds a degree in
Mathematical Physicistfrom the National Autonomous University of Mexicoin and earned his Master of Science
in Engineering with specialization in Microelectronics Digital Signal Processing by the National Polytechnic
Institute in 2005.
Carlos Aquino Ruiz was born in Mexico on April 2, 1973 is in Communications and
Electronics Engineering from the National Polytechnic Institute IPN, a research professor and areas of
development are applied computing, data networking and security.
Dolores Zamorano Saavedra. She is a methodological research and has master's degree in
Educational Sciences. Nowadays it is a research professor at the School of Mechanical and Electrical
Engineering (ESIME) in Mexico. Her areas of development are assessment and project development, scientific
writing and methodology of science