Mobile Terminal Touch Screen Area Segmentation for Accidental Input Filtering

The touch screen is divided into multiple operation areas (first operation area and second operation area) with different response characteristics. The first operation area corresponds to regions where accidental touches are more likely to occur, while the second operation area corresponds to regions where intentional touches are more likely. By segmenting the touch screen into different zones with distinct response strategies, the system can respond quickly to intentional operations in the second area while filtering out accidental operations in the first area, thus maintaining responsiveness while improving operation identification accuracy.

Different response qualities are applied to different regions of the touch screen. The first operation area (edge areas) employs a filtering response strategy where operations are analyzed more carefully before execution, while the second operation area (central areas) employs a direct response strategy. This local differentiation allows the system to maintain high operation recognition completeness in the second area while reducing resource consumption by filtering out accidental operations in the first area, thus optimizing the balance between completeness and energy efficiency.

The touch screen is segmented into first and second operation areas, where the first operation area corresponds to the edge regions with higher accidental touch frequency and the second operation area corresponds to the central regions. This segmentation allows the system to apply different response strategies to different regions, enabling narrow rim design with high screen ratio while mitigating the harmful effect of increased accidental touches in edge areas through selective filtering in the first operation area.

The system performs preliminary determination of operation area and operation type before executing the touch operation response. By pre-establishing the classification framework of first and second operation areas and predefined operation types, the system can quickly categorize incoming touch operations without complex real-time analysis. This preliminary classification simplifies the decision-making process, improving operation distinction accuracy while minimizing the increase in system complexity through structured preprocessing.