PATENT CLAIM ANALYSIS

Application Number: 15860662
Application Type: Utility
Filing Date: 2018-01
Publication Date: 2018-05
Patent Classification: ["382", "106000"]

Abstract:
The present disclosure can provide an image processing apparatus. In some embodiments, the image processing apparatus in accordance with the disclosure comprises memory configured to store a previously selected depth information value (d prev ), (d prev ; d previ ) having been selected for a previously processed fragment and signal processing logic ( 103 ). The signal processing logic is configured to calculate a similarity measure for the current fragment based on a depth information value candidate defining a reference fragment candidate of a digital reference image, compare the depth information value candidate with the previously selected depth information value (d prev ), apply a weighting function to the calculated similarity measure to obtain a weighted similarity measure for the current fragment based on the comparison, and determine whether to select the depth information value candidate as the depth information value (d best ) for the current fragment based on the weighted similarity measure of the depth information value candidate.

Claim (Index 8):
The image processing apparatus ( 100 ) according to  claim 1 , wherein the signal processing logic ( 103 ) is configured to determine the depth information value (d best ) for the current fragment by sequentially processing depth information value candidates (d i ) of a set of depth information value candidates;\n wherein the signal processing logic ( 103 ) is configured to: calculate a similarity measure for a current depth information value candidate (d i ) of the set of depth information value candidates; compare the current depth information value candidate (d i ) with the previously selected depth information value (d prev ; d prev,k ); apply the weighting function to the similarity measure of the current depth information value candidate (d i ) of the set of depth information value candidates to obtain a weighted similarity measure depending on the comparison; compare the weighted similarity measure of the current depth information value candidate with a currently best similarity measure (cost best ) to a currently best depth information value (d best ); when the weighted similarity measure of the current depth information value candidate does not fulfill an update condition with regard to the currently best similarity measure (cost best ) maintain the currently best depth information value (d best ) as currently best depth information value and the currently best similarity measure as the currently best similarity measure, and/or when the weighted similarity measure of the current depth information value candidate fulfills an update condition with regard to the currently best similarity measure (cost best ), write the current depth information value candidate (d i ) as currently best depth information value (d best ) to the memory and write the weighted similarity measure of the current depth information value candidate (d i ) as currently best similarity measure (cost best ) to the memory ( 101 ); and after all depth information value candidates (d i ) have been processed, select the currently best depth information value (d best ) as depth information value (d best ) for the current fragment of the current digital image.

Metadata:
- Claim Count in Document: 19.0
- Percentile: 86.0
- Lexical Diversity: 2.50725
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15860930', '12706245', '14526377', '14144458', '14600402']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3443536649858517
- 35 USC 102 Novelty (BERT): 0.5358766689224561
- Combined Prediction Score: 0.3635059653795122
- Mean Citation Score: 224.91889
- Max Citation Score: 375.23868
- Similarity Product: 272.88807298107145

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

Dataset: test