PATENT CLAIM ANALYSIS

Application Number: 15904517
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2018-12
Patent Classification: ["375", "240120"]

Abstract:
A method, system, and computer program product for compressing an image using similar images includes: receiving a first image; storing the first image on a storage server; comparing the first image to one or more stored intra-frames (I-Frames) to determine a similar I-Frame from the one or more stored I-Frames; in response to determining the similar I-Frame, determining that one or more stored predicted frames (P-Frames) reference the similar I-Frame; comparing the first image to the one or more stored P-Frames to determine a similar P-Frame; determining whether the first image meets a P-Frame threshold level for the similar P-Frame; in response to determining that the first image meets the P-Frame threshold level, generating a first P-Frame for the first image using data from the similar P-Frame and data from the similar I-Frame to compress storage space used by the first image on the storage server.

Claim (Index 1):
A computer-implemented method comprising:\n receiving an image, wherein the image is an uncompressed image; storing the image on a storage server, the storage server storing a plurality of images; comparing the image to one or more stored intra-frames (I-Frames), each of the one or more stored I-Frames corresponding to an image from the plurality of images, to determine a similar I-Frame from the one or more stored I-Frames, wherein comparing the image to the one or more stored I-Frames comprises:\n determining similarity values for each of the one or more stored I-Frames, \n comparing each similarity value from the similarity values to a similarity threshold, wherein the similarity threshold is a number indicating a threshold amount of variance between the image and the one or more stored I-Frames, and wherein the similarity threshold is specified by an owner of the storage server, and \n determining a similarity value from the similarity values that is greater than the similarity threshold; \n in response to determining the similar I-Frame, determining that one or more stored predicted frames (P-Frames) reference the similar I-Frame, wherein determining that the one or more stored P-frames reference the similar I-Frame includes determining that the stored P-Frame was compressed using data from the similar I-Frame; comparing the image to the one or more stored P-Frames to determine a similar P-Frame, wherein the similar P-Frame is a stored P-Frame, from the one or more stored P-Frames, with a similarity value greater than the similarity threshold; determining whether the image meets a P-Frame threshold level for the similar P-Frame, wherein determining whether the image meets the P-Frame threshold level comprises:\n determining the similarity value of the similar P-Frame, and \n comparing the similarity value of the similar P-Frame with the P-Frame threshold level; \n in response to determining that the image meets the P-Frame threshold level, determining whether the image meets a bidirectional predicted frame (B-Frame) threshold level for the similar P-Frame, wherein the B-Frame threshold level indicates a threshold amount of similarity between the image and the similar P-Frame, wherein determining whether the image meets the B-Frame threshold level includes comparing the similarity value of the similar P-Frame with the B-Frame threshold level; and in response to determining that the image meets the B-Frame threshold level, compressing the image into a B-Frame using data from the similar P-Frame and the similar I-Frame, wherein the image is compressed into the B-Frame after the image is stored on the storage server for a predetermined time threshold.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 88.0
- Lexical Diversity: 2.74576
- Patent Class: 375.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15630262', '15810881', '15063240', '14205027', '09844549']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4916068757773104
- 35 USC 102 Novelty (BERT): 0.4988063529847912
- Combined Prediction Score: 0.4923268234980585
- Mean Citation Score: 203.643736
- Max Citation Score: 270.04013
- Similarity Product: 218.8443223967528

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 0
- Claim Label 112: 1
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test