Image Point of Interest Detection via Tile Segmentation

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Solution Overview

Problem

Existing image processing technologies face challenges in identifying and tracking points of interest in real-time image streams, especially in applications like stereoscopic projection, where computational algorithms struggle to recognize complex shapes and maintain processing speed.

Innovation Solution

A method involving dividing images into tiles, identifying pixels with maximum or minimum values, and selecting these pixels as points of interest, which allows for robust and fast feature point detection suitable for real-time applications.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Difficulty of detecting and measuring

If computational algorithms are used to identify points of interest in image streams, then object recognition capability is improved, but processing speed deteriorates

Engineering Contradiction:

Improveobject recognition capabilityVSAvoidprocessing speed

Core Design Contradiction:

Difficulty of detecting and measuringVSProductivity

Solution Approach 1:

The image is divided into multiple tiles or blocks, and points of interest are identified independently within each tile. This segmentation allows parallel processing of different regions, significantly improving processing speed while maintaining recognition capability through comprehensive coverage of all image regions.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent transforms the image data into a different parameter space by calculating gradient magnitudes and directions, then identifies points of interest based on local maxima in this transformed space. This parameter transformation simplifies the recognition task and enables faster processing compared to direct complex shape analysis.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If full spatial resolution is used for point of interest identification, then detection accuracy is improved, but processing resource consumption increases

Engineering Contradiction:

Improvedetection accuracyVSAvoidprocessing resource consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

By dividing the image into tiles and processing each tile independently, the patent reduces the computational burden on each processing unit while maintaining overall detection accuracy. The segmentation enables distributed processing that conserves resources compared to analyzing the entire high-resolution image at once.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent extracts only the essential features needed for point of interest identification by calculating gradient magnitudes and directions, then identifies local maxima. This extraction approach obtains sufficient detection accuracy without processing all pixel data, thereby reducing resource consumption.

Inventive Principle:

Principle #2Taking out (Extraction)

Data Source

PatentUS9977992B2Identifying points of interest in an image

Publication Date: 2018.05.22 GRASS VALLEY LTD

AI summary

Points of interest are identified in an image to characterize that image by dividing the image tiles consisting of adjacent pixels; finding within each tile the position of a pixel with an extremum value and ascribing that extremal value to the tile; identifying a tile with an extremal value which is more extreme than that of all adjacent tiles; and selecting as a point of interest the position within the image of the pixel with the extremum value in that identified tile.