PATENT CLAIM ANALYSIS

Application Number: 16201470
Application Type: Utility
Filing Date: 2018-11
Publication Date: 2019-05
Patent Classification: ["382", "125000"]

Abstract:
A fingerprint image recognition method is provided. The method includes: acquiring a target image from a captured texture image; acquiring a target shape feature corresponding to the target image, the target shape feature being configured to represent a shape feature of the target image; and when the target shape feature matches with a preset finger shape feature, determining to perform a fingerprint recognition on the texture image. Also provided in the present invention are a fingerprint image recognition apparatus and a terminal.

Claim (Index 1):
A fingerprint image recognition method, comprising:\n acquiring a target image from a captured texture image; acquiring a target shape feature corresponding to the target image, comprising: acquiring a sum of pixel values in each row or each column of the target image, the target shape feature being configured to represent a shape feature of the target image; and when the target shape feature matches with a preset finger shape feature, determining to perform a fingerprint recognition on the texture image, comprising: when sums of pixel values corresponding to a preset number of adjacent rows or adjacent columns of the target image are gradually increased or decreased, determining to perform the fingerprint recognition on the texture image.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 98.0
- Lexical Diversity: 2.04545
- Patent Class: 382.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: True
- Related Applications: ['15841055', '16197078', '15593083', '15434385', '14551842']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.291960384193977
- 35 USC 102 Novelty (BERT): 0.4842689031151693
- Combined Prediction Score: 0.3111912360860962
- Mean Citation Score: 194.363618
- Max Citation Score: 206.44254
- Similarity Product: 162.26869964533927

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

Dataset: test