PATENT CLAIM ANALYSIS

Application Number: 15908784
Application Type: Utility
Filing Date: 2018-02
Publication Date: 2019-08
Patent Classification: ["382", "125000"]

Abstract:
A rapid identification method for fingerprint first provides a fingerprint identification apparatus having a fingerprint sensing area and divides the fingerprint sensing area into fingerprint sensing sub-regions. In a registration stage, the method performs fingerprint sensing for the entire fingerprint sensing area to obtain fingerprint image for a whole fingerprint sensing area, fingerprint minutiae and relevant locations for the fingerprint minutiae and then pre-stores those data. In an identification stage, the method performs fingerprint sensing on a part of the fingerprint sensing sub-regions for a user to be identified and detects fingerprint minutiae and relevant locations for the fingerprint minutiae in the part of the fingerprint sensing sub-regions. The method compares the fingerprint minutiae and relevant locations detected in the identification stage with respect to the corresponding fingerprint minutiae and relevant locations in the registration stage in order to determine whether the user can be granted with access right.

Claim (Index 2):
The rapid identification method in  claim 1 , wherein the fingerprint identification apparatus comprises a plurality of sensing electrodes.

Metadata:
- Claim Count in Document: 23.0
- Percentile: 88.0
- Lexical Diversity: 2.68966
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['14866259', '10477050', '15675365', '14942449', '15149222']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3719362963453912
- 35 USC 102 Novelty (BERT): 0.5010234435290299
- Combined Prediction Score: 0.3848450110637552
- Mean Citation Score: 233.941368
- Max Citation Score: 240.39659
- Similarity Product: 164.1188184325636

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