{"id":25113,"date":"2022-11-29T13:15:16","date_gmt":"2022-11-29T07:45:16","guid":{"rendered":"https:\/\/mobisoftinfotech.com\/resources\/?p=25113"},"modified":"2025-12-30T17:56:04","modified_gmt":"2025-12-30T12:26:04","slug":"vehicle-number-plate-detection-mechanism-using-computer-vision","status":"publish","type":"post","link":"https:\/\/mobisoftinfotech.com\/resources\/blog\/vehicle-number-plate-detection-mechanism-using-computer-vision","title":{"rendered":"An Understanding of Vehicle Number Plate Detection Mechanism using Computer Vision"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">AI and computer vision is playing a major role in transportation evolution. Autonomous vehicle technology, fuel injection systems, self-driving cars, <a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/digital-scanning-solutions-for-business\">digital scanning<\/a>, sensing and processing technologies, intelligent transportation systems, etc., are transforming many aspects of human life.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The role of transportation technologies is massive in making bustling cities livable, workable, manageable, safe, and sustainable. Such technologies can be used in different applications in urban areas for sustainable urban mobility. One of the vital application areas is vehicle number plate detection, which captures the information from the number plates via the video or photo footage of cameras and identifies vehicles.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">In today\u2019s post, I will discuss the novel system of vehicle number plate recognition, its use-case, significance, how it works, techniques, etc. Let\u2019s unfold this further and see how computer vision can help recognize vehicle number plates seamlessly.<\/span><\/p>\n\n\n\n<h2>Defining the Vehicle Number Plate Detection&nbsp;<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Number plate detection (NPD) is one such innovative mechanism that identifies a specific part on the vehicle license plate and understands the characters using advanced technologies. It is one of the key functions of intelligent transportation systems.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Known as Registration Plate Recognition (RPR), or License Plate Recognition (LPR), the latest system of Vehicle Number Plate Recognition (NPR) uses AI, ML, deep learning, and computer vision-powered approaches to read such license plates on vehicles without human interaction.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">This advanced system of number plate identification captures an image from a moving vehicle, searches for a number plate, and extracts relevant alphanumerics with the aid of the <a href=\"https:\/\/mobisoftinfotech.com\/products\/digital-scanning-solution\">optical character recognition (OCR)<\/a> mechanism. It translates the characters into readable digital text, which can be used for various applications such as preventing car theft, automated toll tax collection, traffic control, etc.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Authorities can install a number plate recognition mechanism on CCTV in many regions to identify vehicles and control other facets of inspection, traffic management applications, and safety. This automated system helps them track the actual entry\/exit time of a vehicle and the amount of time it spends in a particular region.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Thus, the system can open a wide range of advantages to parking systems along with space management, governance, and vehicle traffic controls in urban areas.&nbsp;<\/span><\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><b>Popular Use Cases of the Automated Vehicle Number Plate Detection System Include the following:<\/b><\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Effective traffic law enforcement<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Vehicle theft prevention<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Journey time analysis<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Automatic parking management (Smart Parking)<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Traffic management and traffic optimization<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Automated collection of tolls and toll booth records&nbsp;<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">To assist visitor management systems in recognizing guest vehicles<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Security monitoring and border crossings<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">A perfect solution while dealing with the new normality distances and touchless sanitary regulations.<\/span><\/li>\n<\/ul>\n\n\n\n<a href=\"https:\/\/mobisoftinfotech.com\/products\/digital-scanning-solution?utm_source=blog_cta&#038;utm_campaign=vehicle-number-plate-detection-mechanism-using-computer-vision-cta1\"><figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"120\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/02\/inline-cta-6.png\" alt=\"Implement Computer Vision Technology for Multiple Application Area\" class=\"wp-image-25114\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"120\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20120%22%3E%3C%2Fsvg%3E\" alt=\"Implement Computer Vision Technology for Multiple Application Area\" class=\"wp-image-25114 lazyload\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/02\/inline-cta-6.png\"><\/figure><\/a>\n\n\n\n<h2 class=\"wp-block-heading\">About Vehicle Registration and Number Plate Format<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Every vehicle has its unique identity, which is represented by its license plate. Vehicle registration is mandatory as it is proof of vehicle ownership acknowledged by the government. The vehicle registration certificate becomes essential for any legal actions to be pursued upon the vehicle.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Talking about the vehicle number plate format, it comprises a numeric or alphanumeric code, which helps identify the vehicle. It has an official registration number, a numeric or alphanumeric character in different colors, fonts, and sizes depending on the country and its rules.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">For example, the current UK number plate format consists of two letters, two numbers, then a space, and further three letters (e.g. \u2013 XX20 XXX), introduced in 2001 for all new vehicles registered.<\/span><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">The first two letters are memory tags representing vehicle registration location, whereas the former represents the region and the latter represents a DVLA local office.&nbsp;<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">The following two numbers are age identifiers, which show the year and six-month period in which the vehicle was registered for the first time. This age identifier changes every six months &#8211; March and September.&nbsp;&nbsp;<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">And the last three letters followed by a space are random letters.&nbsp;<\/span><\/li>\n<\/ol>\n\n\n\n<p><span style=\"font-weight: 400;\">The vehicle number plate format has changed several times and is pliable in the future as per country regulations. Also, different countries have their own set of representations for the number plate format. Using various algorithms of the number plate recognition system, authorities can extract precise vehicle information. Some of the useful algorithms are as discussed below:<\/span><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Optical character recognition to identify characters<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Plate localization to find the plate in image<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Plate orientation and sizing to adjust the dimensions&nbsp;<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Character segmentation to find specific characters on the plates<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Normalization to adjust the brightness as well as the contrast of an image<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Syntactical analysis to check characters and positions against the country-specific rules<\/span><\/li>\n<\/ol>\n\n\n\n<p><span style=\"font-weight: 400;\">The software solves many critical problems such as blurry images, poor file resolution, different fonts, an object obscuring part of the plate, etc. Now, let us understand how number plate detection works.<\/span><\/p>\n\n\n\n<h2>How Does Vehicle Number Plate Recognition System Work?<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">The sole purpose of the automated system is to distinguish vehicles by recognizing number plates. This number plate recognition process is divided into three parts: Identification of vehicle number plate, Plate character recognition and segmentation, and OCR calculation to translate characters into encoded content.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The automatic license plate recognition system consists of digital image capture units (like high-speed cameras with IR filters), application software (like video analytics software), processors capable of performing various object and character recognition, different algorithms to capture information from fast-moving vehicles, and an alert capability to notify operators.&nbsp; The system works like this:<\/span><\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li><b>Moving vehicle number plate identification &#8211;<\/b><span style=\"font-weight: 400;\"> It first detects the vehicles and then captures, normalizes, and enhances the image of vehicle number plates using a series of image manipulation techniques<\/span><\/li>\n\n\n\n<li><b>Number plate character identification &#8211;<\/b><span style=\"font-weight: 400;\"> Then OCR extracts accurate information such as the alphanumerics of the number plates.<\/span><\/li>\n\n\n\n<li><b>Number plate character translation into encoded content &#8211; <\/b><span style=\"font-weight: 400;\"> At last, the software verifies the sequence of those alphanumeric characters, converts them into text format, and stores the database.<\/span><\/li>\n<\/ol>\n\n\n\n<h2>Computer Vision-powered Approaches Used In Vehicle Number Plate Recognition<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">In urban areas, the real traffic environment is complicated. Usually, authorities can not recognize images from the license plate in such surroundings as the images are too vague or of lower quality, i.e., lower than 32X100 pixels and the rotation angle is beyond \u221210\u00b0 to 10\u00b0 or have uneven illumination that affects the recognition results.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Under these conditions, the main objective of the license plate recognition software is to &#8211;&nbsp;<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Detect the License plate location from the vehicle object and&nbsp;<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Extract text from the detected number plate.&nbsp;<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">For seamless vehicle identification, it is mandatory to recognize vehicle number plates precisely. Incorporating innovative computer vision-powered approaches can help achieve the stated goals. Let\u2019s understand the same in detail.&nbsp;<\/span><\/p>\n\n\n\n<h5 class=\"subtitle-list\"><span>1<\/span> <b>Approaches To Detect the License Plate Location From the Vehicle Object<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">The foremost step in extracting vehicle identity is to detect the license plate from the vehicular image using machine learning models.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">In order to detect the license plate from vehicle images, several machine learning models like deep learning architectures based upon convolutional neural networks can be utilized. This problem statement of object detection is indeed a fast-paced progressing research topic in modern AI. Here\u2019s a list of considerable popular approaches:<\/span><\/p>\n\n\n\n<h5><b>1.1 Object detection using Haar-cascade<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">A Haar-cascade classifier is a machine learning object detection program that identifies objects from images and videos. Typically, it slides a square window over an image and, at each location, asks a machine learning algorithm &#8211;&nbsp; &#8220;is this a number plate?&#8221;<\/span><\/p>\n\n\n\n<h5><b>1.2 Single Shot MultiBox Detector (SSD)<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">The SSD algorithm is used to detect objects and segment images, i.e., locate license plates in images using a single deep neural network. It is a technique to create a bounding box (an area) for each segment within an image, allowing exact object detection and segmentation.&nbsp;<\/span><\/p>\n\n\n\n<h5><b>1.3 Histogram of Oriented Gradients (HOG)<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">HOG<\/span><span style=\"font-weight: 400;\"> is widely used for object detection tasks and focuses on extracting features from images to obtain the object&#8217;s shape and structure. <\/span><span style=\"font-weight: 400;\">For the regions of the image, its feature descriptor generates histograms using the magnitude and orientations of the gradient.<\/span><\/p>\n\n\n\n<h5><b>1.4 Region-Based Convolutional Neural Networks (R-CNN)&nbsp;<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">The key concept behind R-CNN&nbsp; is region proposals which are used to localize the objects within an image-based upon their pixel intensities for better detection. The R-CNN consists of a family of approaches differing in the region proposal methods, speed, and performance &#8211;<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">R-CNN<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Fast R-CNN<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Faster R-CNN<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Mask R-CNN<\/span><\/li>\n<\/ul>\n\n\n\n<h5><b>&nbsp;1.5 You Only Look Once (YOLO)<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">YOLO architecture proposes the use of end-to-end neural networks to predict object class probabilities and detect the bounding boxes all at once. This approach potentially beats other real-time object detection techniques by a large margin. State of the art for YOLO has seen many versions and improvements with time, listing here different versions of YOLO proposed till date:<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">YOLO<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">YOLO v2<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">YOLO v3<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">YOLO v4<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">YOLOR (You Only Learn One Representation)<\/span><\/li>\n<\/ul>\n\n\n\n<p><span style=\"font-weight: 400;\">As an outcome of the object detection (here object being the number plate), using any of the techniques as mentioned above, we would obtain the bounding box images of the license plates detected for each supplied vehicle image. Note that we can use pre-trained license plate recognition models or make a training model from real-time data using the above-mentioned algorithmic approaches.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Some of the available datasets for Automatic License Plate Detection are:&nbsp;<\/span><\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li><span style=\"font-weight: 400;\">Indian License Plates Dataset<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">License Plate images Dataset of 500 vehicles captured from rear view<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Dataset of South America Mercosur license plates with images and labels<\/span><\/li>\n\n\n\n<li><span style=\"font-weight: 400;\">Chinese City Parking Dataset<\/span><\/li>\n<\/ul>\n\n\n\n<h5 class=\"subtitle-list\"><span>2<\/span> <b>Text Extraction From The Detected Number Plate<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">Once the vehicle license plate is detected, the subsequent step is to infer the text in the license plate and segment the alphanumeric characters from it to know the vehicle identity.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Text extraction is one of the most important processes for the automatic identification of license plates because if it fails, the vehicle recognition will not be correct. In order to achieve this objective, OCR can be utilized to decipher the text and employ natural language processing that recognizes, translates, and interprets the text effectively.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The OCR algorithms can be based upon traditional image processing techniques or deep learning techniques. The conventional machine learning-based approaches include image pre-processing and cleansing to eliminate noise from the picture, followed by contour detection to detect text segmentation lines.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Various machine learning-based algorithms can then be applied to extract the text from the segmented image. On the other hand, deep learning techniques provide superior results by combining computer vision-based approaches to natural language processing. OCR algorithms predict the bounding box from the extracted textual regions, and such approaches can be broadly categorized into two stages:&nbsp;<\/span><\/p>\n\n\n\n<h5><b>2.1 Textual Region Proposal&nbsp;<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">This is the first stage in OCR wherein the textual regions from the input license plate image are recognized by convolutional neural networks, and the detected regions are enclosed with the bounding boxes. This typically marks an object detection problem, and object detection models can be taken to advantage here.<\/span><\/p>\n\n\n\n<h5><b>2.2 Natural Language Processing&nbsp;<\/b><\/h5>\n\n\n\n<p><span style=\"font-weight: 400;\">The transformer-based language processing, Recurrent Neural Networks, or simply Convolution-based algorithms can be applied further to extract meaningful characters from the extracted text to make a proper interpretation. As an outcome of Optical Character Recognition, the actual license key number can be identified to serve the purpose of vehicle identification.<\/span><\/p>\n\n\n\n<h2>Market Dynamics of Vehicle Number Plate Detection<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Massive growth in the automobile sector, advancements in the processing technologies, development of integrated unmanned aerial vehicles (UAVs), infrastructure growth in emerging economies, increasing allocation of government funds for <a href=\"https:\/\/mobisoftinfotech.com\/resources\/blog\/intelligent-transportation-system-smart-cities\">intelligent transportation systems<\/a>, etc., are expected to propel the vehicle number plate recognition market growth globally.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The adoption rate of the license number plate recognition mechanism has also increased to locate vehicles &#8211; in the defaulter\u2019s list for toll collection purposes, have violated traffic laws, have expired insurance policies, or been stolen.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">The USA and other European countries are actively taking advantage of the computer vision-powered mechanism for security and traffic enforcement applications. The market size was USD 2.3 billion in 2020, which is expected to reach <\/span><a href=\"https:\/\/www.marketsandmarkets.com\/Market-Reports\/anpr-system-market-140920103.html\" rel=\"nofollow noopener\"><span style=\"font-weight: 400;\">USD 3.8 billion by 2025<\/span><\/a><span style=\"font-weight: 400;\">, at a CAGR of 10.0% during the forecast period.<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">Apart from this, the license plate recognition system allows direct connectivity, identifies the full string, automates tasks, and inspects international plate syntax to define the country of origin. It also offers cost-effective, flexible, and scalable storage solutions. With automated systems like parking payment systems, booking systems, electronic toll collection, etc., the AI-enabled tool enhances the experience of end-users. This ultimately drives the growth of the license plate recognition system market.&nbsp;<\/span><\/p>\n\n\n\n<h2>Conclusion<\/h2>\n\n\n\n<p><span style=\"font-weight: 400;\">Vehicle number plate recognition has become a mature technology and is broadly used in various applications serving vehicle detection, localization, and recognition. This computer vision technology captures photographic surveillance and owes the capacity to transform the optical data from the images to identifiable digital information in real-time scenarios. Indeed, this technology provides an easy-to-understand, cost-effective, better, faster, touchless, and frictionless vehicular identification and parking service.&nbsp;<\/span><\/p>\n\n\n\n<p><span style=\"font-weight: 400;\">From automating tasks to managing space, improving the mobility of people and goods, reducing traffic congestion, and managing incidents effectively, the vehicle number plate identification system offers numerous benefits. Get in touch with our experts to implement the vehicle number plate recognition system and enhance the urban mobility experience.<\/span><\/p>\n\n\n\n<a href=\"https:\/\/mobisoftinfotech.com\/contact-us?utm_source=blog_cta&#038;utm_campaign=vehicle-number-plate-detection-mechanism-using-computer-vision-cta2\"><figure class=\"wp-block-image size-full\"><noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/02\/cta-6.png\" alt=\"Implement Computer Vision-Powered Vehicle Number Plate Detection System Faster and Better\" class=\"wp-image-25115\"><\/noscript><img decoding=\"async\" width=\"855\" height=\"363\" src=\"data:image\/svg+xml,%3Csvg%20xmlns%3D%22http%3A%2F%2Fwww.w3.org%2F2000%2Fsvg%22%20viewBox%3D%220%200%20855%20363%22%3E%3C%2Fsvg%3E\" alt=\"Implement Computer Vision-Powered Vehicle Number Plate Detection System Faster and Better\" class=\"wp-image-25115 lazyload\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/02\/cta-6.png\"><\/figure><\/a>\n\n\n<div class=\"modern-author-card\">\n    <div class=\"author-card-content\">\n        <div class=\"author-info-section\">\n            <div class=\"author-avatar\">\n                <noscript><img decoding=\"async\" src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/04\/Pritam1.jpg\" alt=\"Pritam Barhate\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"Pritam Barhate\" data-src=\"https:\/\/mobisoftinfotech.com\/resources\/wp-content\/uploads\/2022\/04\/Pritam1.jpg\" class=\" lazyload\">\n            <\/div>\n            <div class=\"author-details\">\n                <h3 class=\"author-name\">Pritam Barhate<\/h3>\n                <p class=\"author-title\">Head of Technology Innovation<\/p>\n                <a href=\"javascript:void(0);\" class=\"read-more-link read-more-btn\" onclick=\"toggleAuthorBio(this); return false;\">Read more <noscript><img decoding=\"async\" src=\"\/assets\/images\/blog\/Vector.png\" alt=\"expand\" class=\"read-more-arrow down-arrow\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"expand\" class=\"read-more-arrow down-arrow lazyload\" data-src=\"\/assets\/images\/blog\/Vector.png\"><\/a>\n                <div class=\"author-bio-expanded\">\n                    <p>Pritam Barhate, with an experience of 14+ years in technology, heads Technology Innovation at <a href=\"https:\/\/mobisoftinfotech.com\" target=\"_blank\" rel=\"noopener\">Mobisoft Infotech<\/a>. He has a rich experience in design and development. He has been a consultant for a variety of industries and startups. At Mobisoft Infotech, he primarily focuses on technology resources and develops the most advanced solutions.<\/p>\n                    <div class=\"author-social-links\">\n                        <div class=\"social-icon\">\n                            <a href=\"https:\/\/www.linkedin.com\/in\/pritam-barhate-90b93414\/\" target=\"_blank\" rel=\"nofollow noopener\"><i class=\"icon-sprite linkedin\"><\/i><\/a>\n                            <a href=\"https:\/\/twitter.com\/pritambarhate\" target=\"_blank\" rel=\"nofollow noopener\"><i class=\"icon-sprite twitter\"><\/i><\/a>\n                        <\/div>\n                    <\/div>\n                    <a href=\"javascript:void(0);\" class=\"read-more-link read-less-btn\" onclick=\"toggleAuthorBio(this); return false;\" style=\"display: none;\">Read less <noscript><img decoding=\"async\" src=\"\/assets\/images\/blog\/Vector.png\" alt=\"collapse\" class=\"read-more-arrow up-arrow\"><\/noscript><img decoding=\"async\" src=\"data:image\/gif;base64,R0lGODlhAQABAIAAAAAAAP\/\/\/yH5BAEAAAAALAAAAAABAAEAAAIBRAA7\" alt=\"collapse\" class=\"read-more-arrow up-arrow lazyload\" data-src=\"\/assets\/images\/blog\/Vector.png\"><\/a>\n                <\/div>\n            <\/div>\n        <\/div>\n        <div class=\"share-section\">\n            <span class=\"share-label\">Share Article<\/span>\n            <div class=\"social-share-buttons\">\n                <a href=\"https:\/\/www.facebook.com\/sharer\/sharer.php?u=https%3A%2F%2Fmobisoftinfotech.com%2Fresources%2Fblog%2Fvehicle-number-plate-detection-mechanism-using-computer-vision\" target=\"_blank\" class=\"share-btn facebook-share\"><i class=\"fa fa-facebook-f\"><\/i><\/a>\n                <a href=\"https:\/\/www.linkedin.com\/sharing\/share-offsite\/?url=https%3A%2F%2Fmobisoftinfotech.com%2Fresources%2Fblog%2Fvehicle-number-plate-detection-mechanism-using-computer-vision\" target=\"_blank\" class=\"share-btn linkedin-share\"><i class=\"fa fa-linkedin\"><\/i><\/a>\n            <\/div>\n        <\/div>\n    <\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>AI and computer vision is playing a major role in transportation evolution. Autonomous vehicle technology, fuel injection systems, self-driving cars, digital scanning, sensing and processing technologies, intelligent transportation systems, etc., are transforming many aspects of human life. The role of transportation technologies is massive in making bustling cities livable, workable, manageable, safe, and sustainable. Such [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":25126,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_s2mail":"","footnotes":""},"categories":[286],"tags":[2562,2559,2561,2557,2558,2555,2556,2560],"class_list":["post-25113","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-automatic-license-plate-recognition-system","tag-computer-vision-technology","tag-intelligent-transportation-systems","tag-license-plate-recognition","tag-license-plate-recognition-system","tag-number-plate-detection","tag-vehicle-number-plate-recognition","tag-video-analytics-software"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>An Understanding of Vehicle Number Plate Detection Mechanism using Computer Vision<\/title>\n<meta name=\"description\" content=\"Rely on a computer vision-powered vehicle number plate detection system that aims to improve mobility, increase safety, optimize traffic, and make bustling cities livable, workable, manageable, safe, and sustainable. 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