Object Recognition Software Development

Object Recognition Software Development

We develop custom software solutions that identify and categorize objects within images. Powered by computer vision as a service, our software analyzes visual data, extracts features, and matches them with predefined patterns or categories. This technology automates tasks such as inventory management, data input, document digitization, security surveillance, and more.

Our aim is to turn images into the source of valuable insights for business as well as automate tasks related to visual data input, processing, and monitoring.

From Traditional to Next-gen: Types of Object Recognition Software that We Develop

We provide custom development of six major types of object recognition software. Each type has distinct capabilities and applications across various industries, which are explained below, contributing to automation, efficiency, and improved user experiences.

Traditional Computer Vision Approaches

We involve using handcrafted features and algorithms to detect objects based on characteristics like edges, shapes, and textures.It can be used in various industries such as manufacturing for quality control, where it can identify defects in products; in retail for barcode scanning and price tagging; in security systems for detecting unauthorized objects or individuals.

Deep Learning-Based Approaches

We employ deep learning models, particularly Convolutional Neural Networks (CNNs), to learn representations directly from raw data, enabling highly accurate and robust object recognition. It may be applied in autonomous vehicles for detecting pedestrians, traffic signs, and other vehicles; in healthcare for medical image analysis and disease diagnosis; in agriculture for monitoring crop health and identifying pests or diseases.

Object Detection

We do only identify objects but also localize them within an image or video frame, often using techniques like region proposal networks and bounding box regression.It can be employed in surveillance systems for detecting and tracking objects of interest; in retail for automatic product counting and inventory management; in transportation for traffic monitoring and vehicle counting on roads.

Instance Segmentation

Going beyond object detection, our instance segmentation software delineates individual object instances by assigning pixel-level labels, providing more detailed information about object boundaries. It is used in medical imaging for segmenting organs or tumors from surrounding tissues; in autonomous robotics for identifying objects in cluttered environments; in satellite imagery analysis for land cover classification and urban planning.

3D Object Recognition

We develop software that recognizes and understands three-dimensional objects from images or point cloud data, crucial for applications like robotics, augmented reality, and autonomous vehicles. It can be applied in augmented reality and virtual reality for object interaction and scene understanding; in robotics for 3D object manipulation and navigation; in urban planning for building detection and city modeling from LiDAR or stereo images.

Mobile Object Recognition

Optimized for mobile devices, our software provides real-time object recognition capabilities with lightweight models suitable for deployment on smartphones and tablets.It can be utilized in mobile apps for augmented reality experiences such as virtual try-ons and interactive games; in retail for mobile product recognition and comparison shopping; in tourism for landmark recognition and information retrieval.

How Object Recognition Software Elevates Business Operations

You can use our object recognition software as a transformative tool, enabling mimicking human visual perception with profound implications for your business – explore major of them below.

Automation and cost-reduction

Automate tasks such as inventory management, quality control, and security surveillance, reducing manual effort. This leads to faster workflows and cuts labor costs.

Quality Control

Detect defects or irregularities in products during manufacturing processes, ensuring consistent quality and reducing the risk of recalls or customer dissatisfaction.

Enhanced Security

Enhance security measures by identifying and tracking objects of interest, such as unauthorized vehicles or individuals, in transportation and public safety sectors. In manufacturing, our object recognition software detects defects in products, ensuring only high-quality items reach customers, thus safeguarding brand reputation.

Improved Customer Experience

Personalize customer experiences by analyzing preferences and behavior. For example, in retail, our object recognition software recommends products based on recognized items in customer photos or videos. In physical stores, it facilitates cashier-less checkout experiences, reducing waiting times and enhancing convenience for customers.

Who we do it for

We deliver object recognition software with custom functionality, implementing versatile advanced algorithms to analyze visual data, which makes it adaptable to diverse applications as per below.


With our object recognition software development, digital publishing businesses can automatically tag and categorize multimedia content, enabling efficient content organization and search functionalities. It can also facilitate personalized content recommendations based on user preferences and engagement patterns.


Martech businesses can leverage our object recognition software development to analyze images and videos to identify products, logos, or brand assets. This enables targeted advertising, personalized marketing campaigns, and real-time monitoring of brand visibility across digital channels.


We develop object recognition software for fintech businesses to verify identity documents, such as passports or driver's licenses, through image analysis. Additionally, it can automate data extraction from financial documents, enabling faster loan approvals, account openings, and fraud detection processes.


Object recognition software that we develop for healthcare businesses can analyze medical images to detect and diagnose various conditions, including tumors, fractures, and abnormalities. It can also aid in patient monitoring by identifying medical equipment and tracking patient movements within healthcare facilities.

Tech stack

Our tech stack for object recognition software development commonly comprises programming languages, coupled with deep learning frameworks for neural network training and deployment. Additionally, libraries for computer vision and image processing are essential components of the development process.

Programming Languages

Golang, Python, SQL, T-SQL

Technologies / Frameworks / Libraries

Django, Numpy, Pandas, Docker, Airflow, Jenkins, Grafana, Prometheus

ETL Tools

Microsoft SQL Server Integration Services (SSIS)

Data Integration Platforms

Apache Kafka, Apache Airflow

Data Storage and Databases

Microsoft SQL Server, Oracle, PostgreSQL, MySQL, SQLite, Redis, MongoDB, DynamoDB, AWS S3, ClickHouse, Amazon Redshift, Google BigQuery, Snowflake

Data Science

TensorFlow, Keras, Scikit-Learn, Pandas, Numpy, Dask, Matplotlib

Predictive analytics

XGBoost, CatBoost, LightGBM


NLTK, Spacy, DeepPavlov, fastText, Pymorphy2, HuggingFace


ETL Testing, Data Quality, Test Automation

BI tools

Power BI, Tableau


OS: Windows, Linux, MacOS
Methodologies: Agile, Scrum

Our Portfolio

With a focus on innovation and quality, crafting tailored solutions to meet unique business needs, we deliver scalable and robust software solutions to SMBs, enterprises, and startups since 2011.

OCR System Development for a Taxi Business Provider
Access Control System for mobile devices
Development of a custom online banking solution
Medical System Software: Automating record-keeping in medical research

The Lightpoint difference

Delve into key skills that our team possesses to deliver high-quality object recognition solutions tailored to client objectives.


Deep Learning and Computer Vision Expertise

We have an in-depth knowledge of deep learning frameworks to train neural networks and implementing computer vision algorithms for object recognition tasks.

Data Analysis and Interpretation

We are proficient in analyzing large datasets and extracting meaningful insights is essential for refining object recognition models, optimizing performance, and improving accuracy

Research and Innovation

We conduct continual research of computer vision and object recognition technologies, staying updated with the latest advancements and applying novel approaches to improve accuracy and robustness of object recognition systems.


What types of objects can be recognized by object recognition software that you develop?
We build custom software that identifies and tracks objects of various types, including machinery and equipment, vehicles and devices, animals and people, household appliances and everyday items, and more. Moreover, recognition capabilities may cover faces, text, logos, landmarks, specific products, but this is not an exhaustive list. Using advanced AI and ML algorithms, we can implement practically any type of object recognition that your specific case may demand.
What factors should be considered when conceptualizing object recognition software?
Among important factors to consider we would mention identification accuracy, types and variety of objects that need to be identified, compatibility with your tech stack, and scalability needs. But depending on your business tasks more factors may be added. You can book a free call with our team to audit your case and discover more specific items for consideration.
How accurately does object recognition software identify different types of objects?
Though bespoke object recognition systems offer high accuracy, it may vary a bit across different environmental conditions (e.g. lighting, backgroung, angle, etc) and object complexity. We utilize advanced algorithms that adapt to different conditions and versatile training data to ensure maximum accuracy of object recognition.

Get in touch

Contact us to formulate your strategy of object recognition implementation, aligned with your needs, objectives, and resources.

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