Computer Vision Software Development Services
Computer Vision Service offerings for Real-Time Event Detection, Deriving insights from Videos and Images in the cloud.
Computer Vision Software Development Services
Rapid advances in Artificial Intelligence have enabled programs to process countless digital images and videos. With considerable amount of digital data being generated these days in the form of text, audio, video, and images, organizations must equip themselves competently to address the evolving demands of analytics-driven by this change.

We integrate computer vision services as well as train models to identify specific places, people, and objects and categorize them to retrieve valuable information as well as analytics.

Computer Vision Services

Image Segmentation

This process involves segmenting an image into multiple homogeneous regions based on certain similarity parameters, so that each region can be individually analyzed and is different from its neighboring regions. Such categorization helps in tagging people, labeling objects, face recognition, traffic control, and various other tasks.

Object Detection

Object detection is the first stage of intelligent image analysis. Each object consists of several distinguishable properties that the software can use for classification. This, combined with an existing library of images, allows the software to compare, learn and determine valuable techniques to locate similarities and differences and provide accurate detection results. Object detection facilitates processes like automated damage assessment for insurance claims, property maintenance, store inventory management and more.

Contextual Image Classification

Humans can separate a person or object from their surroundings by identifying boundaries and doing a comparative check with memories or records of similar entities. Computers require a certain context to classify things and form a relationship between pixelated regions. This way, signals, and noise are distinguished and pattern recognition can be performed.

Face Recognition

Once the software recognizes an object, in this case — a face, the image is further processed to identify the person by comparing the facial data with existing data. The applications of this technology range across industries like healthcare, traffic management, manufacturing, HR management, security and so on.
Our Process

Acquiring Image Datasets

To initiate the process, we analyze the business goals and create a database of images extracted from multiple sources. Structured, relevant, and quality data is prepared to serve as a guideline for future comparison.

Labelling Datasets

In image processing, labeling helps to make the database more search-friendly. Filtering similar patterns and making object comparisons become more efficient with this method. Variables like color, contour, intensity, and size are used to create labels and organize the data.

Processing The Data

The labeled dataset undergoes a meticulous quality check by being tested against training data. We run a series of automated processes to enhance the images like adding or removing pixels, removing noise, sorting misclassified data, and so on.

Data Augmentation

To improve the training data, the images are modified with a variety of techniques like flipping (horizontally or vertically), cropping, blurring, zooming, and compression to train the model for more accurate image recognition results.

Understanding The Image

In the final stage, the model is able to correctly interpret and categorize the object identified. The software is now adequately trained to recognize images from new input sources. This iterative process ensures that the model continues to enhance its capabilities over time.
Our Process

Acquiring Image Datasets

To initiate the process, we analyze the business goals and create a database of images extracted from multiple sources. Structured, relevant, and quality data is prepared to serve as a guideline for future comparison.

Labelling Datasets

In image processing, labeling helps to make the database more search-friendly. Filtering similar patterns and making object comparisons become more efficient with this method. Variables like color, contour, intensity, and size are used to create labels and organize the data.

Processing The Data

The labeled dataset undergoes a meticulous quality check by being tested against training data. We run a series of automated processes to enhance the images like adding or removing pixels, removing noise, sorting misclassified data, and so on.

Data Augmentation

To improve the training data, the images are modified with a variety of techniques like flipping (horizontally or vertically), cropping, blurring, zooming, and compression to train the model for more accurate image recognition results.

Understanding The Image

In the final stage, the model is able to correctly interpret and categorize the object identified. The software is now adequately trained to recognize images from new input sources. This iterative process ensures that the model continues to enhance its capabilities over time.
Tools & Methods

About Enigma Soft

Enigma Soft is a software development company established in 2016. Enigma Soft provides IT solutions to your business. We have experience of developing and maintaining successful software products. Satisfied clients around the globe bear testimony to the quality of our work

Location

Office # B-8, Second Floor, Siraj Plaza, Main Saidpur Road, Rawalpindi, Pakistan

+92514570733, +923157039544

info@enigma-soft.com