The practice of analysing a series of video frames is known as video processing. Mainly, it is an effective method to implement video filters where the input and output of the system are videos streamed. Moreover, video processing is more largely spread in different real-time applications. Some of them are video codecs, VCRs, video players, DVDs, video scalers, video players.This article is created with the intention to provide the latest research updates like research challenges, areas, trends, etc. on Video Processing Matlab projects!!!

Due to the benefits of several video processing applications, it is expected to improve more in the aspect of accuracy, reliability, processing speed and etc. Majorly, it is used in the research areas of driverless vehicles, deep learning, motion estimation, etc. Our developers are intelligent to develop numerous video analysis applications by fulfilling the needs of active PhD / MS scholars. We know all effective techniques to process video regardless of complexity.

Overview of Matlab for Video Processing

In general, the majority of Video Processing MATLAB techniques utilize temporal correlation between frames of video. Typically, it works on the principle of “state” which computes output based on previous frames. For instance: The techniques used for object tracking depend on predicted information in order to update events that take place in the future.

For building effective video-based applications, use software that supports various processing technologies and algorithms. MATLAB is the best software that supports the essential requirements of current video processing applications. As well, it also overcomes the challenges of current video processing techniques like video mosaicking, object tracking, video stabilization, etc.

Now, we can see the basic steps involved in video processing project development using MATLAB software. Here, we have given only general procedures which differ from your project requirements. If you have selected your project topic, then we prepare an implementation plan for your project. In this, we give a step-by-step procedure to implement proposed video processing work through advanced development technologies like MATLAB. Further, we also do acceptable changes in the plan only if there are requirements.

Video processing MATLAB involves the following steps,

• Step 1 – Collect the video from a surveillance camera
• Step 2 – Show collected video
• Step 3 – Processing of video (pre-processing, segmentation, representation, and classification)
• Step 4 – Write the processed video and store it in database

Next, we can see about Matlab code to read and display video for your project development. Our developers are good to simplify project code even for complex projects. So, we know all possible ways to minimize code work by practicing numerous MATLAB projects.Similar to the read/write code of a video, we are also efficient to handle the processing code of the video. Based on project requirements, we import all necessary modules, libraries, and toolboxes to simplify the code of your project.

How to read the video in Matlab?

Read input video from file by below command

• in_video = VideoReader(‘filename.avi’)

How to display video in Matlab?

Display input video by below command

• implay – Display videos by installing Video Viewer app
• deployableVideoPlayer – Display sequential video frames
• Support various OS-based codecs. For instance: Linux, MAC, Windows

For your reference, here we have given you a list of Matlab tools and toolboxes for video processing. Here, each one has unique functions and features to work on different video processing operations.

One should precisely need to select the toolboxes based on project requirements. When you let our developers implement your video processing matlab project, our developers will appropriately choose the necessary tools and toolboxes of MATLAB. 

Matlab Tools and Toolboxes for Video Processing

• Enable live data collection using Image Acquisition Toolbox. For instance: use scientific cameras and modified industrial cameras
• Use Computer Vision System Toolbox to display vision-specific techniques
• Flexible to collect and show high-resolution video with respect to efficient memory-space and fastness
• Support object identification, Stereo Vision, 3D-point Cloud Processing, Mobile Object Tracking, etc.
• MATLAB enables web cameras to collect and process video

For illustration purposes, here we have given you some important features of the computer vision toolbox. This toolbox is largely recognized in several video processing projects. Likewise, we deeply work on other toolboxes of MATLAB for working with video processing. Only after considering essential research objectives, our developers will select the optimal toolboxes from all possible toolboxes.

Features of Computer Vision Toolbox for Video Processing

• Semantic Segmentation and Object Recognition
  • Semantic Image Segmentation
  • Image Recognition and Classification
  • Learning Approaches for Object Detection (YOLO v2, SSD, and CNNs)
  • Feature-based Object Identification
• Feature Recognition and Extraction
  • Extraction of Feature Descriptor
  • Image Registration and Retrieval
  • Interest Point Recognition and Acquisition
  • Point Feature Similarity Matching
• Multimedia Ground Truth Labelling
  • Web-based Semantic Segmentation
  • Interactive Multimedia Labelling
  • Image Classification
  • Image Instance Segmentation
• Video Tracing and Motion Prediction
  • Camera Motion Recognition
  • Optical Flow Estimation
  • Activity Recognition
• Point-Cloud Processing
  • Geometrical Shapes Construction
  • Video Registration, Visualization, and Preprocess
  • 3D Point-Cloud using Deep Learning
  • Map Construction using SLAM Approach
• Calibration of Camera
  • Execution of Fisheye and Pinhole Camera Models
  • Adjustment of Stereo / Single Camera
  • Camera Extrinsic and Intrinsic Feature Prediction
• Visual SLAM and Motion Structure Analysis
  • Triangulation Video Analysis
  • Stereo Vision Recognition
  • Simultaneous Localization and Mapping (SLAM) Visualization
  • 3D Video Frame Reconstruction

In the above section, we have listed only a sample toolbox with its key features. Now, we can see significant functions that are basically used for operating input video. Each function is intended to perform a specific task for processing video.

By the by, we have selected primary operations of video processing and listed their corresponding functions. The primary operations are image feature extraction, image retrieval, and image display/visualization. Beyond this, we also support you in other important tasks of video processing regardless of complexity.

Matlab Functions for Video Processing

• Store Salient Image Features
  • BRISKPoints
    • Used to store interest points of BRISK by creating an object
  • ORBPoints
    • Used to store key points of ORB by creating an object
  • cornerPoints
    • Used to store corner points by creating an object
  • SURFPoints
    • Used to store interest points of SURF by creating an object
  • binaryFeatures
    • Used to store vectors of binary feature by creating an object
  • KAZEPoints
  • Used to store interest points of KAZE by creating an object
  • MSERRegions
    • Used to store regions of MSER by creating an object
• Image Retrieval
  • invertedImageIndex
    • Used to create search index by mapping visual words to images
  • vision.BlockMatcher
    • Used to predict the translation/motion among video frames and images
  • evaluateImageRetrieval
    • Used to assess search results of the input image
  • retrieveImages
    • Used to create set of search images for comparable image
  • vision.AlphaBlender
    • Used to integrate overlay images, handpicked pixels, and images
  • vision.LocalMaximaFinder
    • Used to identify local maxima by using matrices
  • estimateGeometricTransform3D
    • Used to forecast 3-D geometric transformation by utilizing matching point pairs
  • bagOfFeatures
    • Used to create objects for a bag of visual words 
  • estimateGeometricTransform2D
    • Used to predict 2-D geometric transformation by utilizing matching point pairs
  • vision.TemplateMatcher
    • Used to find the template in image
• Image Display and Visualization
  • insertShape
    • Used to add shapes over input video or image
  • showMatchedFeatures
    • Used to visualize respective feature points
  • implay
    • Used to play image series / movies / videos
  • insertText
    • Used to add text over input video or video
  • vision.ChromaResampler
    • Used to upsample or downsample chrominance images components
  • showShape
    • Used to showcase shapes over input point-cloud, image or video
  • montage
    • Used to display Multi-image frames in the form of rectangular montage
  • insertMarker
    • Used to add markers over input video or image
  • vision.GammaCorrector
    • Used to eliminate or implement gamma correction over input videos or images
  • insertObjectAnnotation
    • Used to interpret video stream, grayscale image or true color image

Due to the incredibly positive impact of video processing, it is strongly recognized in several application areas. You can find the footprints of video processing in several research fields such as image processing, computer graphics, computer vision, artificial intelligence, and many more. For your information, here we have given you some important real-time applications of video processing. If you want to know more real-time application ideas then approach our team. 

Video Processing Applications

• Customized Recommender System for Medicinal Purposes
• Sensor-based Medical Video Processing for Smart Healthcare
• Prediction and Analysis of Physiological Sign for elder Observation

Now, we can see the important technical challenges of developing a video processing project using MATLAB. These challenges give you numerous project ideas for developing video processing. Further, if you want to develop challenging research ideas to create milestones in your video processing project career then help you to achieve your ambition. In this, we provide appropriate advanced solving solutions and make your developed work more efficient than others. Further, we also support other emerging research challenges in video processing.

Research Challenges in Video Processing

• Real-time Wireless Video Streaming
• Processing of Analog / Digital Signal and Solve by Deep Learning Techniques
• Multi-Variable Issues in Signal Processing and Solve by Optimization Techniques
• Fusion Methods for Image Enhancements in Medical Applications
• Various Compression Methods for Video Processing
• Security Challenges over Video Processing and Solve by Encryption, Stenography, and Watermarking

With an intention to create the best video processing techniques, integrate video scalers with video processors. As well, it improves the quality of video signals by executing below specified tasks. Our developers have sufficient practice on all these techniques. Moreover, we support you not only on these techniques but also on other modern techniques. So, you can strongly believe us to create the best research solutions for your proposed video processing project. Further, we have also given you some important video processing techniques and algorithms.

Latest Video Processing Techniques

• Contrast Enhancement
• Deinterlacing
• Inverse-Telecine
• Frame Rate Adaptation
• Digital Zoom and Pan
• Motion Compensation
• Detail and Edge Enhancement
• ColorPoint Alteration
  • 600 to 710
  • 710 to 600
• Aspect Ratio Management
• Color Space Transformation
  • RGB to Ypbpr/Ycbcr
  • Ypbpr/Ycbcr to RGB
• Mosquito and Block Noise Minimization
• Primary and Secondary Color Tuning
  • Brightness or Hue or Saturation Controls
• Gamma and Sharpness Adjustments

Latest Algorithms used in Video Processing

• Faster R-CNN
• KLT Detection Technique
• Efficient and Accurate Scene Text
• Gaussian Mixture and Average Models
• Multiple Moving Object Tracking
• Single Shot Detector

One best example of the tracking process is the KLT detection technique. The main aim of this project is to track every point of the targeted object for identifying the object’s location. Further, we have also listed some significant research areas of video processing using Matlab. These areas are suggested by our field experts only after reviewing current research articles and journal papers. This helps us to recognize the research interest and requests of current scholars and final-year students.

Latest Research Areas in Video Processing Matlab Simulink

Object Recognition and Counting

In any video processing Matlab project, object recognition is an important process. It is used to recognize and count moving objects in the sequential frames of video. For instance: developed countries use video footage to count wildlife population

Example: Water-birds Population Estimation

Object Tracing

In any video processing Matlab projects, object tracing is the first and foremost process in many applications. For instance: augmented reality, pedestrian avoidance, surveillance, and security. It tracks the moving object in a video from a static camera.

Example: Multiple Moving Object Tracing

In addition, we can see the latest research trends in video processing. These trends are also collected from our deep study of the video processing field. In order to let you realize the video processing research trends, we have addressed only a few research perceptions. Beyond this, we have a huge collection of video processing projects using Matlab. Further, we are also passionate to develop research ideas from future research directions of video processing.