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Content-based Image Retrieval (CBIR) Solution for a World-leading Engineered Surfaces Company

About the Client

The client is a globally renowned name in engineered surfaces and operates in multiple countries worldwide.

Problem Overview

The client approached tech Mahindra to simplify the laminate identification process and make it more efficient. The existing process was manual and it was a time-consuming task to identify laminates from a large laminate repository. The laminates were in multiple colors, textures and patterns. The large variety turned identification more complex.

The project also required to enhance the functionality of the existing mobile application and support similarity check function.

Solution

The Tech Mahindra AI experts developed an AI-powered mobile application solution to search, match and display laminates similar to existing laminates. They performed a live demonstration of application capabilities to the client.

The team used the DeNoise model to enhance laminate images. The model cleaned the image captured by the mobile application and provided a sharper and better image to extract the laminate features. This improved the accuracy of the image identification process.

From the enhanced laminate image, latent features such as pattern, color and texture were extracted using an AI-powered solution. These extracted features were further matched with the features of laminate images present in the repository.

Value Delivered

The solution enhanced the laminate identification efficiency of the application. It reduced manual efforts, minimized human errors and increased productivity resulting from process automation. The hit ratio for identifying correct laminate images based on the given input shot up to 92%. The AI-powered mobile application was more user-friendly which improved customer experience significantly.

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