Brand Logo Detection & Authentication Software

In the realm of intellectual property protection and brand integrity, the application of artificial intelligence (AI) for brand logo detection and authentication has become essential. This technology aids businesses in safeguarding their visual identity, detecting unauthorized usage, and ensuring brand consistency across various platforms.

INFORMATION
Use Case
Logo Detection
Industry
Fashion
DETAILS
Challenge

Streamlining the Process of Brand Logo Similarity Detection

The client routinely interacts with brand logo databases, and the manual process of searching and recognizing brand logos is arduous and time-intensive. They required a proficient system to automate and refine these processes, eliminating the need for manual searches.

Our expert team, specialising in computer vision and image analysis software development, embarked on this project by meticulously analysing use cases, reviewing existing solutions, and, crucially, exploring brand logos data sources. This constituted the preliminary phase of our three-stage plan: investigation, model development, and experimental testing of ideas.

In response, our team delved into the capabilities of machine learning algorithms and the availability of brand logo data to discern logo similarities and potential instances of brand plagiarism, with the aim to present a probability-ranked list of brand logo infringements.

We harnessed the power of computer vision algorithms, focusing on embedding learning to fulfil this need.

Solution

Enhanced Visual Search for brand logo Similarity and Plagiarism Detection

We initiated the development by crafting and evaluating a neural network model capable of predicting encoded vectors for images within a shared vector space, allowing us to quantify the similarities between them.

With access to unlabelled data from the client and public domains, our engineers ingeniously extracted relevant information from brand logo images for the solution. By tackling indirect and nuanced tasks of visual classification, we fine-tuned the model to adeptly learn and identify subtle plagiarism in brand logos.

The culmination of our efforts was grounded in the philosophy that the expansive field of computer vision offers a plethora of methodologies that could elevate the quality of our solution. Through a battery of trials employing both high- and low-level graphic processing techniques, including OCR, we significantly bolstered the model's proficiency in plagiarism detection. The amalgamation of these successful approaches crystallized into the resolution of the client's challenge.

Results

 Deploying Computer Vision for Enhanced brand logo Similarity and Plagiarism Identification

The client now employs a state-of-the-art solution to automate the search and detection of brand logo similarities and brand plagiarism.

The advantages realised from this solution include:

     1. Automated processes for searching brand logo similarities.

     2. Efficient detection of brand plagiarism.

     3. Increased speed of workplace procedures.

     4. Reduced manual workload for employees.

Techstacks Used

Technologies and Tools
Machine Learning: TensorFlow, PyTorch, AutoML Computer Vision: OpenCV, TensorFlow Object Detection API Deep Learning: TensorFlow, PyTorch, Keras Infrastructure: AWS, Azure, GCP, NVIDIA CUDA, Docker, Kubernetes Data Storage: AWS S3, Azure Blob Storage, PostgreSQL, NoSQL databases Data Ingestion: IoT Devices, UAVs/Drones, API Integrations Development: Python, C++, Jupyter Notebooks, Git CI/CD: Jenkins, GitLab CI Monitoring: Grafana, Kibana, Prometheus, PagerDuty, ELK Stack Deployment: TensorFlow Serving, ONNX, Terraform, Ansible.

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