Optical Sensor Histogram Skewness for Mixed-Object Distance Sensing

The patent segments the histogram data by calculating skewness to identify and separate the target object's reflected light component from non-target objects. By dividing the mixed histogram into distinct segments based on skewness characteristics, the system can accurately measure distance to the target object even when multiple objects are present in the measurement region.

The patent changes the parameter of histogram analysis by introducing skewness calculation as an additional parameter. Instead of relying solely on the standard histogram peak, the system uses skewness to detect and correct for distortion caused by non-target objects, thereby improving measurement accuracy in complex environments.

The patent enhances the simple histogram peak detection by adding skewness as a correction parameter. This parameter change allows the system to maintain relative computational simplicity while significantly improving accuracy by compensating for distortion effects through a single additional calculation step.

The patent replaces complex multi-step signal processing mechanisms with a more efficient mathematical approach using skewness calculation. Instead of using elaborate filtering or segmentation algorithms, the system substitutes a relatively simple statistical parameter calculation that achieves similar or better distortion correction with less computational overhead.