Broadcast Signal Channel Change Detection via Mute-Interval Analysis
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Solution Overview
Problem
Existing methods for detecting channel change events in electronic devices are inefficient and inaccurate, often requiring continuous analysis of signal frames, leading to high CPU and memory usage, and struggle to differentiate between channel changes and image stops.
Innovation Solution
An electronic apparatus and method that utilizes audio and video analysis to identify mute intervals and compare feature information before and after the mute interval, combined with the detection of channel change messages, to accurately detect channel changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous analysis of every signal image frame is performed to detect channel changes, then detection coverage is improved, but CPU and memory usage increase significantly
Solution Approach 1:
The patent implements periodic sampling of image frames at predetermined intervals rather than continuous analysis of every frame. The processor is configured to obtain current and previous image frames at specific time intervals, which reduces the frequency of analysis while still maintaining effective channel change detection capability.
Solution Approach 2:
The patent extracts and analyzes only specific critical elements from image frames rather than processing the entire frame data. By focusing on key visual elements and changes, the system achieves accurate channel change detection with reduced computational load compared to analyzing every pixel in every frame.
2Reliability
If conventional image analysis methods are used to detect channel changes, then detection capability is maintained, but the system cannot differentiate between channel changes and image stops
Solution Approach 1:
The patent incorporates feedback mechanisms where the processor continuously compares current image frame analysis results with previous frame data and system state information. This feedback loop enables the system to distinguish between temporary image stops (where content remains static) and actual channel changes (where content transitions to different programming), improving detection reliability.
Solution Approach 2:
The system performs preliminary analysis of image frame characteristics and establishes baseline data before making channel change determinations. By pre-processing and storing reference information about content characteristics, the system can quickly differentiate between genuine channel changes and temporary display interruptions without requiring extensive real-time computation.
Data Source
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AI summary
An electronic apparatus is provided. The electronic apparatus includes a memory configured to store computer executable instructions, an interface, a display, and a processor configured to, by executing the computer executable instructions control the display to display an image corresponding to a broadcasting content input through the interface, based on a mute interval being detected by analyzing an input signal, compare a signal before the mute interval with a signal after the mute interval and identify whether the signals before and after the mute interval are continuous, and identify an occurrence of a channel change event in which the broadcasting content is changed to another broadcasting content based on the identification.