Pixel Vector Encoding for Object Recognition
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Solution Overview
Problem
Current image processing methods lack a systematic approach to determine the relations between pixels, relying on assumptions rather than objective characteristics, which limits the ability to recognize objects and shapes in images effectively.
Innovation Solution
A method for encoding image pixels by generating a vector that includes data from the pixel and its surrounding pixels, arranged to reflect their spatial relationships, allowing for a numerical description of each pixel that accounts for its brightness, color, and temporal variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pixel relationships are encoded using vectors including surrounding pixel data, then object recognition accuracy is improved, but processing complexity increases
Solution Approach 1:
The patent divides the image processing task into pixel-level operations, where each pixel is independently encoded with a vector containing its own data and surrounding pixel data. This segmentation allows complex relationship encoding to be performed through simple, repetitive vector operations at each pixel location, reducing overall processing complexity while maintaining high recognition accuracy.
Solution Approach 2:
The patent transforms pixel data from simple brightness values into vectors that include multiple parameters (pixel value and surrounding pixel values). This parameter expansion enables the system to capture spatial relationships and object characteristics more effectively, improving object recognition accuracy without requiring complex processing architecture.
2Loss of information
If vectors include data from multiple surrounding pixels, then spatial relationship information is improved, but data processing time increases
Solution Approach 1:
The patent performs pixel encoding in advance, creating vectors that pre-include spatial relationship information from surrounding pixels. This preliminary encoding of spatial relationships eliminates the need for complex post-processing operations to extract spatial information, thereby reducing overall data processing time while preserving complete spatial relationship data.
3Manufacturing precision
If pixel encoding uses surrounding pixel data, then object shape recognition is improved, but hardware resource requirements increase
Solution Approach 1:
The patent replaces complex hardware-based image processing systems with a software-based vector encoding approach. By encoding pixel relationships into vectors that include surrounding pixel data, the system achieves improved object shape recognition through algorithmic processing rather than requiring additional hardware resources or complex mechanical imaging systems.
Data Source
AI summary
A method for encoding pixels of digital or digitized images, i.e., images consisting of a set of image dots, named pixels in two-dimensional images and voxels in three-dimensional images, each of said pixels or voxels being represented by a set of values which correspond to a visual aspect of the pixel on a display screen or in a printed image. According to the invention, the pixels or voxels of at least one portion of interest of the digital or digitized image or each pixel or voxel of the set of pixels or voxels which form the image is uniquely identified with a vector whose components are given by the date of the pixels or voxels to be encoded and by the data of at least one or at least some or of all of the pixels around the pixels to be encoded and arranged within a predetermined subset of pixels or voxels included in the whole set of pixels or voxels which form the image.