PATENT CLAIM ANALYSIS

Application Number: 15913246
Application Type: Utility
Filing Date: 2018-03
Publication Date: 2019-09
Patent Classification: ["382", "103000"]

Abstract:
Various aspects of an image-processing apparatus and method for object boundary stabilization in an image of a sequence of image frames are disclosed. The image-processing apparatus includes an image processor that receives a depth image of a scene from a first-type of sensor and a color image of the scene from the second-type of sensor. The scene may comprise at least an object-of-interest. A first object mask of the object-of-interest is generated by a depth thresholding operation on the received depth image. Dangling-pixels artifact present on a first object boundary of the first object mask, are removed. The first object boundary is smoothened using a moving-template filter on the color image. A second object mask having a second object boundary is generated based on the smoothening of the first object boundary. The object-of-interest from the color image is extracted based on the generated second object mask.

Claim (Index 9):
The image-processing apparatus according to  claim 8 , wherein said at least one image processor is further configured to find pixels with a maximum image gradient along a normal to said first object boundary within said moving-template filter, wherein said normal to said first object boundary define a direction in which image gradients are computed.

Metadata:
- Claim Count in Document: 1.0
- Percentile: 90.0
- Lexical Diversity: 2.5
- Patent Class: 382.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15361723', '13055727', '13808388', '15259175', '13129864']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3673924509538411
- 35 USC 102 Novelty (BERT): 0.4764770930375614
- Combined Prediction Score: 0.3783009151622131
- Mean Citation Score: 198.104004
- Max Citation Score: 211.32817000000003
- Similarity Product: 178.64060596995952

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