SS&C Technologies has been granted a patent for a method involving analyzing digital image content. The method includes extracting visual features, executing an image query, and using a matching algorithm to identify objects. The patent also involves assigning template predictions based on descriptor vectors and histograms of digital images. GlobalData’s report on SS&C Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on SS&C Technologies, was a key innovation area identified from patents. SS&C Technologies's grant share as of February 2024 was 65%. Grant share is based on the ratio of number of grants to total number of patents.
Image recognition and classification based on visual features
A recently granted patent (Publication Number: US11868394B2) outlines a method for classifying physical objects based on digital images using computer vision algorithms. The method involves assigning template predictions based on multi-dimensional descriptor vectors and histograms generated from keypoints identified in the digital image. These template predictions are then reconciled, merged where in agreement, and eliminated where not, to classify the physical object based on the remaining prediction. The process includes generating keypoints, comparing descriptor vectors, and utilizing different computer vision algorithms to enhance accuracy.
Furthermore, the patent describes a system implementing this method, comprising a processor, communication interface, and memory storing instructions for performing the classification operations. The system assigns template predictions based on descriptor vectors and histograms, reconciles them, and classifies the physical object accordingly. Additionally, the system can extract visual features, determine clusters, and generate histograms to improve the classification process. The system can receive digital images from mobile devices and process frames of videos containing objects, showcasing versatility in application. Overall, the patent presents a comprehensive approach to object classification using computer vision algorithms and keypoint analysis, with potential applications in various fields requiring accurate object recognition.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
