Qualcomm incorporated (20240121521). IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION simplified abstract
Contents
- 1 IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION
Organization Name
Inventor(s)
Eran Pinhasov of Zichron Yaakov (IL)
Scott Cheng of Foothill Ranch CA (US)
Anatoly Gurevich of Haifa (IL)
IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240121521 titled 'IMAGE PROCESSING BASED ON OBJECT CATEGORIZATION
Simplified Explanation
The abstract describes a patent application for applying different settings for image capture to different portions of image data. An image sensor captures image data of a scene and sends it to an image signal processor (ISP) and a classification engine for processing. The classification engine identifies different object image regions and confidence regions in the image data, allowing the ISP to apply different settings to different portions of the image data based on these regions.
- The patent application involves capturing image data of a scene using an image sensor.
- The image data is processed by an image signal processor (ISP) and a classification engine.
- The classification engine identifies different object image regions and confidence regions in the image data.
- The ISP applies different settings to different portions of the image data based on the identified regions.
Potential Applications
This technology could be applied in various fields such as surveillance, autonomous vehicles, medical imaging, and photography.
Problems Solved
This technology helps in improving image processing accuracy and efficiency by applying different settings to different portions of the image data based on object and confidence regions.
Benefits
The benefits of this technology include enhanced image classification, improved image quality, and optimized image processing.
Potential Commercial Applications
The potential commercial applications of this technology include camera systems, security systems, medical imaging devices, and industrial automation equipment.
Possible Prior Art
One possible prior art for this technology could be the use of image processing algorithms to enhance image quality and classification accuracy.
Original Abstract Submitted
examples are described for applying different settings for image capture to different portions of image data. for example, an image sensor can capture image data of a scene and can send the image data to an image signal processor (isp) and a classification engine for processing. the classification engine can determine that a first object image region depicts a first category of object, and a second object image region depicts a second category of object. different confidence regions of the image data can identify different degrees of confidence in the classifications. the isp can generate an image by applying a different settings to the different portions of the image data. the different portions of the image data can be identified based on the object image regions and confidence regions.
