Figure 1. The license plate localization using histogram Figure 2. Illustration of template matching algorithm Pattern of letter “K” on the more detail can be illustrated in the figure below: Figure 3. Illustration of a letter pattern 4. The Proposed Method In this paper, we propose to use histogram for license plate localization and template matching for recognition. The flowchart of the proposed method is showed in Figure 4. Figure 4. The proposed method flowchart The input image should be RGB image. First the RGB image will be converted into grayscale image using Equation 1[10]. The dilation process is then applied to the image to make the characters thicker. The next step is vertical edge processing. This will process the image vertically by creating the vertical histogram. This histogram, represents the sum of differences of gray values between neighboring pixels of an image, row-wise. (1) Where = 0.299 = 0.587 = 0.114 Y = Grayscale value Figure 5. Vertical Edge Processing The image parts that have vertical histogram value under the average value will be eliminated, so the image will be segmented into row per row (Figure 5). After that, the remaining parts of the image that is connected to the top or bottom of the image are removed because the license plate is impossible connected to the top or bottom of the image. Then the most probable row candidate will be chosen by selecting the row by maximal value of the vertical histogram. The result is illustrated in Figure 6. Figure 6. Result of vertical edge processing The next process is horizontal edge processing. This will process the image horizontally by creating the horizontal histogram. This histogram, represent the sum of differences of gray values... ... middle of paper ... ...capture configurations comparison Figure 15. The screen shoots that showed recognition of police number A. Testing of License Plate Detection From all samples, there are 63 successfuly detected samples (78.75%) while original Naikur Bharatkumar Gohil method achieves 28,75%. License plate is successfuly detected if it covers all police number characters. The successfuly detected plate examples are shown in Figure 16 and Figure 17. Figure 16. Plate Number object that successfully detected 1 Figure 17. Plate Number object that successfully detected 2 The remaining failed detected license plates are those whose image is cut or exceed the police number area. Some examples of failures in detecting license plates are shown in Figure 18 - 20. Figure 18. Cut license plate Figure 19. License plate area exceeded Figure 20. Cut and license plate area exceeded B.
Scott Robinson moved from Houston to Cincinnati in 2007. Before leaving, Mr. Robinson sold his Hyundai Santa Fe to a used car dealer in Rosenberg, Texas. Due to clerical errors at the dealer, Scott's car was sold with his license plates still attached to the vehicle. The new owner of the vehicle ran a stoplight and when the license plate was read, Mr. Robinson's information was pulled up. When he finally received his ticket, it was too late for him to protest the charges even when providing proof of sale for the vehicle.(Geor...
This officer ran the vehicle's license plate and determined it was registered to Miryha Smith. This officer confronted Smith about the spelling of her first name and she stated "It depends on who spells it." This officer asked Smith what name appears on her driver's license she stated "I don't know" This officer ran the license number attached to license plate return and confirmed Smith lied about the spelling of her first name.
When it comes to personal privacy, I believe that license plate scanners should only be lawful for official police activities. In the article “Private License Plate Scanners Amassing Vast Databases Open to Highest Bidders” RT a media platform funded by the Russian government, argues that it’s the Wild West in terms of how companies can collect, process, and sell this data. Conversely, the publication “In These Times’, a progressive activism journal out of Chicago, argues in their article “Who Has the Right to Track You?” that legislation would create a safe haven for certain criminals. These alternative viewpoints are presented quite differently, however, people whose lives are affected by this need to sit down and think of meaningful ways we should or should not regulate this.
Have you ever been pulled over by a police officer where you were given a ticket? If you have that is one part of their job. Traffic enforcement is one of the most recognizable and universal police responsibilities. Marked police cars are easy to see and most Americans have been stopped for a traffic violation. Some of these violations are s...
These points are presented in a vivid golden color and are done to create a contrast to the organization that the purple dots represented. Not only are these points stenciled in amongst the dots, but also in the non-dotted focal point as well. This gives a sense of disorder to the previously established order by the dots, and even disrupting the clarity provided by the non-dotted focal point.
... A Laser Scanner does not have to be in contact with a scanner tag to use it. A standard reach Laser Barcode Scanner can read an institutionalized ID from something like 6 to 24 inches away, and a long go Scanner can read one from something like 2 to 8 feet away. Certain extra long-enlarge Laser Barcode Scanners are prepared for examining a scanner tag from up to 30 feet away. Laser Barcode Scanner are regularly in handheld or "firearm" structure components, yet are additionally normally assembled for ledge or settled mount provisions.
After the initial pre processing steps of smoothening and removal of noise, the edge strength is calculated by taking the gradient of the image. For the purpose of edge detection in an image, the Sobel operator first performs a 2-D spatial gradient measurement with the help of convolution masks. The convolution masks used is of the size 3X3, where one is used to calculate the horizontal gradient(Gx) while the other is used to calculate the vertical gradient(Gy). Then, the approximate absolute edge strength can be calculated at each point. The masks used for the convolution process is as shown
For the extraction of the depth map includes three parts, image block motion Extraction, color segmentation, Depth map average fusion.
This approach includes two processes, training and classification (Chelali, Djeradi & Dejradi, 2009). In the training process, a subspace will be established by using the training samples, and then the training faces will be projected onto the same subspace. In the classification process, the input face image will be measured by Euclidean Distance to the subspace, and a decision will be made, either accept or reject.
[Jain, 2004] Jain, A.K.;Ross, A.;Prabhakar, S.;"An introduction to biometric recognition", Volume: 14 Issue: 1 Issue Date: Jan. 2004, on page(s): 4 - 20
with a digital map, who shows the position of the car. Based on the position of
...detecting the dark regions in the image. Based on the detected pair of eye candidates, possible facial regions are located by means of the geometric relationship between various features. Detection of eyes, mouth and nose are done by estimating the probable region for each feature. Geometrical interpretation of location of facial features, used in the algorithms is described with pictorial representation. It is observed that, with the use of facial geometry, the accuracy of features (eyes, nose and mouth) detection is greatly improved. The proposed method for feature extraction is also found to be accurate in detecting all kinds of frontal images. In conclusion, this method can achieve a high performance in detecting human faces and extracting facial features.
“Each light has a different preset wavelength designed to detect hair, fibers, and body fluids at crime scenes, these lights allow a crime scene to be processed faster and more thoroughly than ever before.” This technology is speedy and can help locate the whereabouts of criminals. The use of in-car camera systems has become very popular, especially by law enforcement. These cameras are used to record traffic stops and road violations of civilians. “From the time the first in-car cameras were installed to document roadside impaired-driving sobriety tests, the cameras have captured both intended and unintended video footage that has established their value. Most video recordings have resulted in convictions; many provide an expedited means to resolve citizen complaints, exonerate officers from accusations, and serve as police training videos.” Photo enforcement systems helps to maintain road safety by “automatically generating red light violations and/or speeding summons and as a result to greatly improve safety for the motoring public.” (Schultz,
(c). Hanks. P. 2000. The Basics of Loop Vehicle Detection. [ONLINE] Available at: http://www.marshproducts.com/pdf/Inductive%20Loop%20Write%20up.pdf.html. [Accessed 01 December 13].
From the point of view of the application, the digital image is presented as a matrix I that are consist of r = 1, and so on, R is rows and j = 1, and so on, C is columns. For that, the elements of the matrix that are carry intensity values. By that, depending on the type of image will make the matrix consists only have of one layer (a grey tone image) or several layers (coloured, multispectral, and hyperspectral images). A colour table is an alternative form of an image decription.