Generally, video processing is intended to deliver top-quality visible-light video for computer vision, pattern recognition, or pattern analysis. The majority of digital video processing techniques are inherited from image processing techniques. Therefore, learning image processing theories and technologies is the best way to acquire a strong technical foundation in digital video processing. Both video and image processing are jointly creating countless real-world applications in many scientific developments.

Are you searching for the best video processing project ideas? Then this page helps you to find unique research perspectives of video processing!!!

Digital video processing requires so much computation power due to its workload. Since it deals with processing and analyzing the sequence of frames. However, balancing power resources (like battery life) is a challenging task in the current mobile video communication field. Further, we have given you some important attributes of video processing in the below list. 

Video Processing Attributes

• Frame – Single image of the video. For instance: 1/30 or 1/25 seconds
• Shot – Series of similar frames. For instance: one event or basic video units
• Scene / Clip – Series of continuous shots utilizing action, time, and space
• Episode – Series of successive scenes. For instance: complete incident-based frames, etc.

Now, we can see about the noise reduction in the video. Since real-time video processing handles a large volume of data. Therefore, the possibility of noise and artifacts is more in raw input data. So, it requires to improve video quality by removing unwanted noise in the video. Moreover, it also reduces the dimension of data to acquire less data for processing. 

For your information, here we have given you some important noise reduction methods that are widely used in video processing projects. Likewise, we also support you in other important operations of real-time video processing.

Different Types of Noises in Video 

• Thermal Noise
• Composite Triple Beats (CTB)
• Single-Frequency Modulation Distortion
• Impulse Noise (Great Energy and Short Time)
• Composite Second-Order Beat (CSO)

Solving out latest research issues will help in formulating video processing project ideas. Next, we can see significant research issues of video processing. All these issues are collected from recent research areas. When you deal with video sequences, it includes different types of artifacts particularly in old videos due to aging. Here, we have given you two main issues that are globally looking for effective solutions to solve. Let’s look at below to know this. 

Research Issues in Video Processing 

• Intensity Flicker
  • Frame intensities may create unexpected temporal variation which is not a part of the original scene
• Blotches
  • High aging and mistreating of video frames may create dark spots, irrelevant brightness

Our developers have designed the most suitable research techniques for solving these issues. Moreover, we also support you in all other emerging research issues in video processing. For your information, here we have given you some constant artifacts that are largely found in a digital video sequence. In this, we have also included the source and implication of artifacts in real-world scenarios. 

Our developers are intelligent to recognize probable artifacts in raw data to remove them efficiently. Since it is the primary step for any sort of video processing application. Based on implication, we determine the complexity level of reducing artifacts in video signals. Then, we suggest appropriate solutions to perform the perfect pre-processing process in your project. 

Common Artifacts in Video Sequences

• Ringing
  • Source – Ideal Filters Usage
  • Effects – Generate high-contrast edges and rippling
• Simple Blockiness / Block Edge Impact
  • Source – DCT co-efficient for coarse quantization in block-aided compression
    • For instance:  MPEG-1 and M-JPEG
  • Effects – Intensity gap over nearer block limitations in decrypted frame
• Mosquito Noise
  • Source – Compression Method Impairment
  • Effects – High-contrast Edges and Chrominance Level Variation
• False Contour / Edges 
  • Source – Amplitude levels in coarse quantization 
  • Effects – Create a noticeable impact on edges in the frame (Need transition of smooth intensity)
• Color Exploitation and Blurring 
  • Source – Compression Method Impairment
  • Effects – Complex Edges / Texture, Color Smearing, and Spatial Loss

One of the most important factors which differentiate video processing from still images is motion. This factor is currently in need best manipulation techniques for adapting still image methods to video processing project ideas. These expected techniques are needed to be efficient in producing the best visual experience for the user in the aspects of 2D projection and 3D object motions. 

A good video processing technique will make you analyze and interpret video by all means. For instance: motion estimation is the preliminary step of video processing. In this, it is required to determine the color intensity and object motion intensity. For your information, here we have given you significant video processing techniques for enhancing image quality.

Video Processing Techniques 

• B-Splines
• Histogram
• Stereo Imaging
• Point Operations
• Hough Transform
• Linear Filtering
• Edge Detection
• Template Matching
• Sampling Theorem
• Video Restoration
• Video Compression
• Digital Image Coding 
• Nonlinear Image Filtering
• Video Enhancement
• Discrete Fourier Transform

As mentioned earlier, motion is the thin line of difference between video processing and still image. By the by, it mainly addresses the 3D objects along with their 2D projections. Here, the motion has a key player role to decide on video processing and analysing techniques. 

For instance: intensities movements can be computed by motion estimation algorithm. Further, we have also itemized important techniques used for motion estimation in video processing. If there is a need, we also design new algorithms to solve complexity. 

Motion Estimation Techniques for Video Processing

• Computation of Kernel Density 
• Normalized Running Gaussian 
• Eigen Backgrounds
• Gaussian Mixture 

If you are curious to know more about 3D moving objects and their implication, then connect with us. We are here to provide the finest guidance with detailed information in your requested areas. You can use us as the best platform to clarify your queries in every aspect of video processing. 

Our resource teams are friendly to approach and informative to gain more knowledge about up-to-date video processing project ideas. This makes our handhold clients choose us every time. Also, we ensure you that our proposed techniques in solving your research problem are always optimized to achieve the best results in the development phase. 

Optimization Methods for Video Processing                      

• Multi-resolution (Discrete and Continuous) Search
• Exhaustive Search Optimization
• Gradient-Based Search Approach 

What is real-time video processing?

Processing real-world video and image has turned out to be a more complex task due to its high computation. Since it deals with a large volume of data that are expressed in the form of an image. Further, it requires effective solutions to handle complex operations in video processing. 

How to do Real-Time Video Processing? 

Now, we can see in what way real-world video processing is working. 

For that, assume that you are going to implement an object detection model based on the drone’s live video input. Here, it uses a deep learning technique to collect video from drones. By the by, drones have recently become an important commercial application that ranges from asset check-ups to military observation. Particularly, the current developments of artificial intelligence (AI) make the drone industry grow everywhere. 

• Smart Phone
  • Use smartphones which are capable to connect with the RC controller of drone
  • For instance: a phone with DJI drones compatibility
• GPU-based Computer with WiFi Adapter
  • Used to display drone-captured video
  • For that, implement a deep learning model
  • Suggested to use GPU-based computer for better results
  • Also, GPU-based computer increases the speed of inference time

The process can be broken down into 3 parts:

• Acquire the captured video of a drone 
• Implement object recognition model over drone video 
• Show obtained results in output screen of a computer-assisted system
• Train and test your proposed object recognition model for identifying new objects

Next, we can see about the top 2 demanding Video Processing Project Ideas. These ideas are intended to address the current research direction of video processing. Beyond this, we have loads of projects ideas for the best video processing project in your research career. Once you share your interested areas, then we provide you with information about advancements.

In the below list, we have also included vital entities of each research area. Our developers are great at analyzing every aspect of proposed areas. For instance: In video partitioning, camera breaks are analyzed through general techniques but camera actions and regular transitions require advanced techniques to handle issues.

Top Two Interesting Video Processing Project Ideas 

• Video Partitioning / Segmentation
  • Video-Shot Extraction and Editing Impact Classification
    • Camera Actions – Zoom, Panning, and Slanting
    • Camera Discontinuities – Rapid Transitions
  • Regular Transitions – Fade-in, Dissolves, Fade-Out, Wipes
• Video Retrieval / Accessibility
  • Content-level and Structure-level Video Retrieval
    • Content-level – Retrieval based on audio elements, object elements (shape, color, size), camera motion, scenes, object motion, etc.
    • Structure-level – Retrieval based on scenes, episodes, and shots

In addition, we have also given you extensively used development tools and technologies of video processing. From our coding experience, we identified following tools are sophisticated with lots of libraries and modules. 

All the incorporated features are efficient to manage both simple and complex video processing applications. These tools are not only preferred by our experts but also requested by our handhold scholars and final-year students. Further, we extend our development service in other growing technologies too. Mainly, we have an objective to meet your expectation and make you satisfied with our delivered experimental results.

Development Tools for Video Processing 

• Matlab
  • Able to integrate low-cost web cameras for acquiring live video
  • Provide algorithms to manipulate and validate captured video
  • Scalable to configure with another computing device by setting acquisition parameters
  • For instance: color space, device properties, region of interest, frames per trigger, etc.
  • Offer Image Acquisition Toolbox to perform many sorts of functions for generating blocks and connecting lidar sensors/cameras with Matlab Simulink
  • Execute video processing operations such as data frames reading, writing, analyzing, etc.
  • For instance: moving object detection and counting in video
  • Video Processing Steps in Matlab
    • Load record into Matlab
    • Split record into individual frames utilizing camera resolution
    • Define background through video’s mixed frames
    • Implement transient model to relate color values with each frame background (based on absolute error values)
    • Use error values to compute mixing time and define with homogeneity metrics
• OpenCV
  • Able to collect a live stream of data from the camera
  • Offer interfaces like cv2.VideoCapture () and cv2.VideoWriter() methods to write opencv scripts in python
  • Execute process over video in a frame-by-frame format
  • For each second there will be multiple frames
  • To capture video, use cv2.VideoCapture() which has arguments as video name or device index
  • To display frame, use cv2.waitKey() with approximate time
• AutoESL
  • Enable FPGA-based Image and Video Processing Platform (IVPP)
  • Use Micro Blaze processor for configuring video interface blocks in RTL
  • Support multi-video resolutions using Micro Blaze processor
  • Without altering front-end and back-end, IVPP know the logic to plug in with video interface blocks
• Simple Video Camera Frame Grabber Toolkit
  • Offer FrameGrabM toolkits to collect still frames from a live video source
  • For instance: USB webcam or FireWire video camera
  • Here, consider video frames as RGB matrix in Matlab
  • Utilizes java library called LTI-CIVIL for image capturing

To sum up, we provide you with trending video processing project ideas from advanced research areas for your ambitious PhD / MS study. Then, we assist you to choose the best-fitting implementation tool and dataset based on your handpicked project needs. Next, we wisely develop your project in simplified code. We assure you that we finish your on-time with accurate outcomes. At the end of development, we also assess the efficiency of your proposed techniques through different performance metrics. In this way, we practically prove your proposed research objectives with acceptable shreds of evidence. So, connect with us to accomplish your research target.