Abstract: A liquid level detection system of detecting a target container includes a main body, an optical sensor, a fan and an operational processor. The main body has a supporting platform whereon the target container is disposed. The optical sensor is disposed above the supporting platform and adapted to output a detection image containing the target container. The fan is disposed on the main body and faces the supporting platform. The operational processor is electrically connected to the optical sensor, and adapted to analyze the detection image generated within an operation period of the fan and further to acquire an effective feature of the target container inside the detection image.

Abstract: One object determining system comprising: an air ejection device, configured to eject air; a distance detecting circuit, configured to detect distances between an electronic device comprising the object determining system and at least one location of an object when the air ejection device ejects air to the object; and a determining circuit, configured to determine a type of the object according to variations of the distances.

Abstract: A dirtiness level determining method applied to an electronic device comprising an image sensor. The method comprises: (a) capturing a first image at a first time point according to first type of light; (b) capturing a second image at a second time point after the first time point according to the first type of light; (c) calculating a first fixed pattern according to a first difference between the first image and the second image; and (d) calculating a first dirtiness level of the image sensor according to the first fixed pattern; (e) generating a first notifying message if the first dirtiness level is higher than a dirtiness threshold.

Abstract: A tire surface managing method, comprising: emitting detecting light to a target object on a surface of a tire; receiving reflected detecting light from the target object and from the surface adjacent to the target object; determining whether the target object protrudes according to a distance calculated according to the reflected detecting light from the target object and a distance calculated according to the reflected detecting light from the surface; determining whether the target object forms a hole on the surface according to the distance calculated according to the reflected detecting light from the target object and the distance calculated according to the reflected detecting light from the surface; receiving the reflected detecting light from the surface to calculate a width of the hole on the tire; and activating a protection mechanism for a vehicle comprising the tire if the width is larger than a width threshold.

Abstract: There is provided a cleaning robot including a light source module and an image sensor. The light source module projects a horizontal line pattern toward a moving direction. The image sensor captures, toward the moving direction, an image of the horizontal line pattern. The light source module is arranged below the image sensor so as to eliminate the interference from second reflection.

Abstract: An auto clean machine, comprising: an optical sensor; a light source, configured to generate a first light pattern; and a processing circuit, configured to determine which light pattern is the first light pattern if the optical sensor senses more than one light pattern.

Abstract: A control apparatus for an auto clean machine comprising a light source configured to emit light to illuminate at least one light region outside and in front of the auto clean machine. The control apparatus comprises: a first image sensing area, configured to sense a first brightness distribution of the light region, wherein a resolution for a first direction of the first image sensing area is higher than a resolution for a second direction of the first image sensing area; and a processor, configured to control movement of the auto clean machine according the first brightness distribution.

Abstract: An optical navigation device comprising: a processing circuit; a first light source, configured to emit first light; a cover; at least one second light source, configured to emit second light toward the cover; and an first optical sensor, configured to sense first optical data generated according to the first light and to sense second optical data generated according to the second light on the cover. The processing circuit determines a dirtiness level of the cover based on the second optical data sensed by the first optical sensor. The optical navigation device can further comprise a second optical sensor. Also, an optical navigation device which can avoid the interference of another optical navigation device is also disclosed.

Abstract: An image capturing device comprising an image sensor. The image sensor comprises: a first sensing region, having a first sensing threshold; and a second sensing region, having a second sensing threshold lower than the first sensing threshold. At least one object image is determined to be invalid when the object image captured by the first sensing region has brightness formation lower the first sensing threshold. At least one the object image is determined to be invalid when the object image captured by the second sensing region has brightness formation lower the second sensing threshold. The present invention also discloses a distance measuring device using the image sensor.

Abstract: An image recognition system includes a processing module, a sensor module, and a database. The sensor module is electrically connected to the processing module. The database is electrically connected to the processing module. The sensor module configured for capturing at least one image. The at least one image is stored in the database. The processing captures a contour of an object from the at least one image and separates the contour of the object into a plurality of portions. A plurality of arrangements is defined between the portions of the contour of the object. The processing module determines a state of the contour of the object based on the arrangements.

Abstract: An object surface managing method comprising: (a) emitting detecting light to the groove via alight source; (b) receiving first reflected detecting light from the surface and second reflected detecting light from a bottom of the groove via a light sensor; and (c) calculating a groove depth of the groove according to the first reflected detecting light and the second reflected detecting light.

Abstract: An optical device, comprising: a processing circuit; a light source, configured to emit light to a surface; and an optical sensor, configured to sense optical data generated based on reflected light or scattering light of the light. The processing circuit computes a dirt level of the surface according to the optical data.

Abstract: An image recognition system includes a processing module, a sensor module, and a database. The sensor module is electrically connected to the processing module. The database is electrically connected to the processing module. The sensor module configured for capturing at least one image. The at least one image is stored in the database. The processing captures a contour of an object from the at least one image and separates the contour of the object into a plurality of portions. A plurality of arrangements is defined between the portions of the contour of the object. The processing module determines a state of the contour of the object based on the arrangements.

Abstract: There is provided a moving robot including a first light source module and a second light source module respectively project a first light section and a second light section, which are vertical light sections, in front of a moving direction, wherein the first light section and the second light section cross with each other at a predetermined distance in front of the moving robot so as to eliminate a detection dead zone between the first light source module and the second light source module in front of the moving robot to avoid collision with an object during operation.

Abstract: An image noise compensating system, comprising: a distance determining device, configured to determine whether a distance is larger than a distance threshold or not; an image sensor, comprising at least one image sensing unit, wherein the image sensor forms a combined image sensing unit when the distance is smaller than the distance threshold and senses images without forming the combined image sensing unit when the distance is larger than the distance threshold, wherein a width of an area that the combined image sensing unit can sense is larger than a width of an area that the image sensing unit can sense; a noise compensating circuit, configured to compensate image noises; and a control circuit, configured to calculate a location of the image noise compensating system.

Abstract: There is provided an image processing device including a light sensor and a processor. The light sensor is used to detect light and output an image frame. The processor identifies intensity of ambient light according to an image parameter associated with the image frame. When the ambient light is identified to be strong enough, the processor performs an object identification directly using the image frame. When the ambient light is identified to be not enough, the processor firstly converts the image frame to a converted image using a machine learning model, and then performs the object identification using the converted image.

Abstract: A detecting device for detecting liquid or colloid, comprising: a light emitting device, configured to emit first light, wherein a first angle between a first emitting direction of the first light and a surface when the detecting device is located on the surface, wherein the first angle is larger than 0° and smaller than 90°; an optical sensor, configured to detect first optical data generated based on the first light; and a processing circuit, configured to determine if the liquid or the colloid exists in a predetermined range of the detecting device based on the first optical data. An automatic cleaner applying the detecting device is also disclosed.

Abstract: There is provided a moving robot including a light projector, an image sensor and a processing unit. The light projector projects a vertical light segment toward a moving direction. The image sensor captures, toward the moving direction, an image frame containing a light segment image associated with the vertical light segment. The processing unit calculates a step distance and a segment feature according to the image frame, outputs a flag signal according to the segment feature to indicate whether the calculated step distance is confident or not, and perform a pixel interpolation in calculating the step distance to improve the identification accuracy.

Abstract: There is provided a cleaning robot including a first light source module and a second light source module respectively project a first light section and a second light section, which are vertical light sections, in front of a moving direction, wherein the first light section and the second light section cross with each other at a predetermined distance in front of the cleaning robot so as to eliminate a detection dead zone between the first light source module and the second light source module in front of the cleaning robot to avoid collision with an object during operation.

Abstract: A method for eliminating misjudgment of a reflective light applied to an autonomous robot is provided. The autonomous robot includes a driving system and an optical sensing system that includes a light source and a light sensor. The light source emits a transverse linear light as detection light and the light sensor senses reflective light signals from an object that reflects the detection light. In the method, a frame image including the reflective light signals is captured by the light sensor, characteristics of the reflective light signals are analyzed, and the characteristics of the reflective light signals can be corrected based on the characteristics of previous reflective light signals stored in a memory of the autonomous robot in order to exclude abnormal information. The object can be confirmed based on the corrected characteristics of reflective light signals. The misjudgment caused by the abnormal information can therefore be eliminated.