Computer Vision Services & Solutions

Computer Vision Algorithms & Applications

Uniwebb Software develops advanced and innovative applications by integrating computer vision services into other softwares such as RPA, ERP, CRM, CMS, POS, CCTV, and diagnostic software to detect irregularities in production lines, analyze x-ray or other medical images, identify products and people on social media etc. Our professional team of data scientists and AI engineers has developed custom computer vision apps with advanced components such as optical character recognition (OCR), object classification, feature recognition, segmentation, pattern recognition, object detection, filtering etc. to address the business challenges of a variety of industries.

Here’s some of our computer vision capabilities

Computer Vision is the process of training a computer to see

Digital Image Acquisition and Processing

You can acquire image in visible, infrared, ultraviolet, x-ray, gamma-ray, and radio-wave bands or it may be formed from sound as in medical ultrasound imaging or from some other source.

Face recognition/ detection & Tracking

We can find, analyze, organize, and tag faces in photos based on attributes like age, gender, emotion, smile, pose, etc.

Facial Expression & Gesture Classification

Emotions and facial expressions have an extremely important role in communication between humans. We can monitor and analyze these human emotions and facial expressions to detect your customer’s sentiments.

Video analytics

Our experts can Analyze video content in real-time, extract metadata, send alerts/notifications and a whole lot more by eliminating the need for manual monitoring.

Optical character recognition

Automatically scans documents like PDF files, paper documents, or images via digital camera and converts into editable and searchable data.

Image processing

Analyze images in real-time to detect objects and people and extract rich information to classify

How can you apply computer vision solutions?

By digitizing printed and handwritten documents in cases where text is written backwards, or hidden within a complex shape, or obscured by pictures. Here if will be difficult to make out the individual characters — a process that is called Optical Character Recognition (OCR).

In our approach

Define the text area

we first define the text area by various computer vision methodologies

Apply OCR

then apply OCR to extract the text. In this process, each individual case is unique in the fonts used, and language improvements may be required to get the most accurate character recognition output.

We have hands-on experience in OCR, and successfully implemented this technology in numerous cases.

An example of our work is Chart Recorder, where we developed an algorithm to capture data from gas flow charts. In this process each trace on the chart was identified and an output table with all required metrics of pressure, water and temperature was generated.

We can apply the same technique to a varieties of other domains such as:

Computer vision example for Banking:

We can build an application to transmit any amount of data from paper documents to a database source for continued processing.

Computer vision example for Retail:

To build an application to automatically verify ID cards and birthdays for age restricted items like tobacco and alcohol and or gated portals.

Object recognition on photos and videos

We apply machine learning and computer vision technologies for object recognition. Generally computer vision is used for some tasks and more complex projects may require machine learning, deep learning, neural networks, or a combination of both technologies.

Other applications may be developed to detect specific events when video streaming. A good example is in manufacturing facilities and constructions sites for performance comparison of various states using computer vision.

We can build similar algorithms in high-precision industries like high-precision machining and manufacturing from tolerances in the single -digit micron range to ultra-precision involving tolerances in the sub-micron range to forecast equipment breakdown.

We can also implement use it in the pharmaceutical and biotech industries to ensure accurate drug dosing.

We can use object recognition in the ecommerce domain to recognize products from images, and search for similar products. Further we can define item sizes, their shapes and positions to determine the exact size and shape required to place it in a warehouse, and therefore optimize the storage space and increase its capacity. Another application in commerce is item placement, to check whether or not that item is placed in its proper location in the storage or warehouse.

Controlling product quality

Quality control is an essential building block of any successful business that delivers products that meet or exceed customers' expectations. Computer vision supercharges quality control to execute efficiently in a diverse range of environments. Automatic inspection of finished products for defects to enhance the quality of packaging.

Got a project in mind?

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