Abstract: There is provided a mobile robot that performs the obstacle avoidance, positioning and object recognition according to image frames captured by the same optical sensor. The mobile robot includes an optical sensor, a light emitting diode, a laser diode and a processor. The processor identifies an obstacle and a distance thereof according to image frames captured by the optical sensor when the laser diode is emitting light. The processor further performs the positioning and object recognition according to image frames captured by the optical sensor when the light emitting diode is emitting light.

Abstract: An auto clean machine comprising: a height computing device; and an obstacle determining device. The height computing device is turned on to compute a height or an overhang height of an obstacle when the obstacle determining device determines the obstacle exists in a predetermined region of the auto clean machine. The height computing device does not compute the height and the overhang height when the obstacle determining device does not determine the obstacle exists in the predetermined region.

Abstract: There is provided a smoke detector including a light source, a reflective surface, a light sensor and a processor. The light sensor receives reflected light when the light source emits light toward the reflective surface, and generates a reference detection signal when there is no smoke. The processor receives the detection signal from the light sensor, and automatically selects a set of predetermined condition thresholds according to a profile of the detection signal to be compared with the detection signal thereby determining whether to generate an alarm according to the comparison result.

Abstract: An electronic system including a display device, an image sensor, a face detection engine, an eye detection engine and an eye protection engine is provided. The image sensor captures an image. The face detection engine recognizes a user face in the image. The eye detection engine recognizes user eyes in the image. The eye protection engine turns off the display device when the user eyes are recognized in the image but the user face is not recognized in the image.

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: An electronic apparatus, comprising: an optical sensor, comprising a kind determining region and an element analyzing region, wherein the optical sensor acquires first optical data via the kind determining region, and acquires second optical data via the element analyzing region, wherein the kind determining region and the element analyzing region are different regions of the optical sensor; a kind determining component, configured to determine an object kind of the object according to the first optical data; and an element analyzing component, configured to analyze element of the object according to the second optical data.

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: There is provided an electronic device including a light source module, an image sensor and a processor. The light source module projects a first pattern and a second pattern toward a moving direction. The image sensor captures an image of the first pattern and an image of the second pattern. The processor calculates one-dimensional depth information according to the image of the first pattern and calculates two-dimensional depth information according to the image of the second pattern.

Abstract: There is provided an optical distance measurement system including an image sensor and a processing unit. The processing unit is configured to generate an image to be calculated according to at least one image captured by the image sensor, wherein different image regions of the image to be calculated correspond to different exposure times thereby improving the accuracy of the distance calculation.

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: There is provided a smoke detector including a light source, a reflective surface, a light sensor and a processor. The light sensor receives reflected light when the light source emits light toward the reflective surface, and generates a reference detection signal when there is no smoke. The processor receives the detection signal from the light sensor, and automatically selects a set of predetermined condition thresholds according to a profile of the detection signal to be compared with the detection signal thereby determining whether to generate an alarm according to the comparison result.

Abstract: An electronic system including a display device, an image sensor, a face detection engine, an eye detection engine and an eye protection engine is provided. The image sensor captures an image. The face detection engine recognizes a user face in the image. The eye detection engine recognizes user eyes in the image. The eye protection engine turns off the display device when the user eyes are recognized in the image but the user face is not recognized in the image.

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 dirtiness level determining method, applied to a robot cleaner comprising an image sensor, comprising: capturing an image of a reference surface as a reference image: capturing a current image; calculating a fixed pattern according to a difference between the reference image and the current image; calculating a dirtiness level of the image sensor according to the fixed pattern; and generating a notifying message if the dirtiness level is higher than a dirtiness threshold. The dirtiness level of the image sensor can be automatically determined by the robot cleaner, thus the user can be notified before the auto clean machine cannot normally operate.

Abstract: An object determining system, comprising: an optical sensor, comprising a kind determining region and an element analyzing region, wherein the optical sensor acquires first optical data via the kind determining region, and acquires second optical data via the element analyzing region, wherein the kind determining region and the element analyzing region are different regions of the optical sensor; a kind determining circuit, configured to determine an object kind of the object according to the first optical data; and an element analyzing circuit, configured to analyze element of the object according to the second optical data.

Abstract: 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; a first image sensing area, configured to sense a first brightness distribution of the light region; a second image sensing area below the first image sensing area, configured to sense a second brightness distribution of the light region; and a processor, configured to control movement of the auto clean machine according the first brightness distribution and the second brightness distribution. The processor generates a wall detection result based on the first brightness distribution of the light region, generates a cliff detection result based on the second brightness distribution of the light region, and controls the movement of the auto clean machine according to the wall detection result and the cliff detection result.

Abstract: There is provided a cleaning robot including a light source module, an image sensor and a processor. The light source module projects a line pattern and a speckle pattern toward a moving direction. The image sensor captures an image of the line pattern and an image of the speckle pattern. The processor calculates one-dimensional depth information according to the image of the line pattern and calculates two-dimensional depth information according to the image of the speckle pattern.

Abstract: There is provided an optical distance measurement device including a processor embedded with a first algorithm and a second algorithm. The first algorithm is used to calculate an object depth when an obstacle is distanced from the distance measurement device smaller than a predetermined distance. The second algorithm is used to calculate an object depth when the obstacle is distanced from the distance measurement device larger than the predetermined distance.

Abstract: A material determining device comprising a first image sensor, a second image sensor, and a light source is provided. The material determining method comprises: (a) sensing a first image by the first image sensor according to light from the light source; (b) sensing a second image by the second image sensor according to the light; and (c) determining whether material corresponding to material images in the first image and the second image is first type of material or second type of material, according to locations of the material images in the first image and the second image and according to shapes of the material images in the first image and the second image. By this way an electronic device using the material determining device can properly operate according to the type of material.

Abstract: An imaging system includes a light source, an image sensor and a processing unit. The image sensor alternatively captures a first bright image, a first dark image, a second bright image and a second dark image, wherein the first bright image is captured with a first exposure time corresponding to activation of the light source within a first time interval, the first dark image is captured with the first exposure time corresponding to deactivation of the light source within the first time interval, the second bright image is captured with a second exposure time corresponding to activation of the light source within a second time interval, and the second dark image is captured with the second exposure time corresponding to deactivation of the light source within the second time interval, wherein the second exposure time is longer than the first exposure time.