Pixart Imaging Incorporated

Au Optronics Corporation

Skhynix Inc.

Guo-Zhen Wang

Han-Chang Lin

Nien-Tse Chen

Ming-Tsan Kao

En-Feng Hsu

Yi-Pai Huang

Tse-En Peng

Ren-Hau Gu

Shiaw-Yu Jou

Ming-Ching Ma

Shuan-Yu Tung

Hui-Hsuan Chen

Chih-Ming Sun

Wei-Chung Wang

Chi-Chieh Liao

Cheng-Nan Tsai

Hung-Ching Lai

Shih-Feng Chen

Ting-Yang Chang

Hung-Wei Tseng

Yen-Chang Chu

Feng-Chi Liu

Ching-Kun Chen

Chia-Yi Liu

Pi-Cheng Wu

Shih-Chin Lin

Chang-Sheng Chiu

Yi-Lei Chen

Hung-ching Lai

Chi-Mao Hung

Yu-Hao Huang

An-Thung Cho

Min-Feng Chiang

Jiun-Jye Chang

Cheng-Chiu Pai

Tsung-Fa Wang

Wei-Min Sun

Tsung-Hsien Hsieh

Shu-Wen Tzeng

Wei-Lung Liao

Yi-Chien Wen

Tsung-Wei Pai

Hsuan-Ku Chen

A smoke detector comprises a light source, an optical sensor, a first, and a second processing circuit. The optical sensor senses optical data and comprises; a first oscillator, generating a first oscillating signal; and a second oscillator, generating a second oscillating signal. The first processing circuit generates a first command to instruct the first oscillator to oscillate for a first expected oscillating time, and acquires a first real oscillating time, wherein the first processing circuit further computes a time relation between the first expected oscillating time and the first real oscillating time. The first processing circuit generates a second command to instruct the second oscillator to oscillate for a second expected oscillating time according to the time relation. The second processing circuit controls the smoke detector to generate a first alarm according to the time relation. The optical sensor can also be applied to other electronic devices.

Smoke detector and optical sensing system

An optical sensing system and an optical sensing method are provided. The system includes a bright-field light source, a dark-field light source, an optical detecting circuit, and a processing circuit. The processing circuit performs a floor type detection process, including: controlling the dark-field light source to provide dark-field illumination; receiving, by the optical detecting circuit, scattered lights of the dark-field light source; executing a dark-field computation process to obtain a first optical characteristic, and determining whether the first optical characteristic meets a first surface condition; in the negative, determining that a floor is a first type; in the affirmative, controlling the bright-field light source to provide bright-field illumination; receiving, by the optical detecting circuit, scattered lights of the bright-field light source; executing a bright-field computation process to obtain a second optical characteristic, and determining whether the second optical characteristic meets a second surface condition.

Optical sensing system and optical sensing method

Disclosed are a distance measuring method and a distance measuring apparatus. During the distance measuring, an image is obtained. If the location of a center of gravity of the image is within a first segment, the calculating unit calculates a distance between the object and the distance measuring apparatus corresponding to the projection point, according to a first mapping relationship and the location of a center of gravity of the image. If the location of a center of gravity of the image is within a second segment, the calculating unit calculates a distance between the object and the distance measuring apparatus corresponding to the projection point according to a second mapping relationship and the location of a center of gravity of the image.

Distance measuring method and apparatus

An electronic device, comprising: a first light source, configured to emit first light; a second light source, configured to emit second light; a first optical sensor, configured to sense first optical data generated based on reflected light of the first light; a light guiding device, configured to receive the second light; and a second optical sensor, configured to sense second optical data generated based on the second light emitted by the light guiding device. The first optical sensor and the second optical sensor can be integrated to a single optical sensor.

Electronic device which can determine a dirtiness level

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.

Material determining device, material determining method, autonomous cleaning device

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 whether the object is a rigidity type object or a soft type object according to the variations.

Object determining system and auto clean machine using the object determining system

An optical sensing system, comprising: a first light source, configured to emit first light to a first position; a second light source, configured to emit second light to a second position, wherein the first position is above the second position, wherein the first light is not emitted to the second position and the second light is not emitted to the first position; and an optical sensor, configured to sense optical data generated based on at least one of the first light source and the second light source; wherein a detecting region of the optical sensor comprises an upper half region and a lower half region, wherein a size of the upper half region is adjustable.

Optical sensing system

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.

Auto clean machine and auto clean machine control method

An object determining system, comprising: a processing circuit; a first stage object sensor, for generating a first stage object sensing result of an object; and a second stage object sensor, for generating a second stage object sensing result of the object if the processing circuit determines the object exists in a predetermined range based on the first stage object sensing result, wherein the processing circuit further determines an object kind of the object based on the second stage object sensing result; a line light source; and an area light source. The first stage object sensor generates the first stage object sensing result based on the line light. The second stage object sensor generates the second object detecting result based on the plane light. The first stage object sensor is a depth sensor or a thermal sensor. The second stage object sensor is an image sensor or a thermal sensor.

Object determining system and robot cleaner applying the object determining system

An optical sensing system is provided. The optical sensing system includes a first light source, a second light source, a light sensor, and a processor. The processor is configured to: control the first light source to scan a horizontal detection area; control the light sensor to capture a first frame by receiving first reflective lights from the horizontal detection area; obtain a first reflection pattern, and analyze the first reflection pattern to determine whether an object is within the first portion; if so, control the second light source to scan a first vertical detection area; control the light sensor to capture a second frame from the first vertical detection area; process the second frame to obtain a second reflection pattern, and analyze the second reflection pattern to determine whether the object is detected by a misjudgment.

An eye state detecting method, applied to an electronic apparatus with an image sensor, which comprises: (a) acquiring a detecting image via the image sensor; (b) defining a face range on the detecting image; (c) defining a determining range on the face range; and (d) determining if the determining range comprises an open eye image or a close eye image.

Eye state detecting method and eye state detecting system

An image processing method includes: acquiring a plurality of sensed values based on detecting light; comparing sensed values of each row with a corresponding threshold value to select a plurality of selected sensed values from the plurality of sensed values; determining a location of a centroid according to the plurality of selected sensed values; and calculating a plurality of depth values with respect to a plurality of detecting points according to the location of the centroid and a plurality of depth information transformation functions respectively corresponding to the detecting points.

Image processing method and system for optical distance measurement

An image recognition method and system based on deep learning are provided. The image recognition system includes a first recognizing engine, at least one second recognizing engine and a processing circuit. The second recognizing engine is activated to recognize an image when the first recognizing engine is recognizing the image. The processing circuit determines whether to interrupt the first recognizing engine recognizing the image according to a result outputted by the second recognizing engine after the second recognizing engine completes recognition of the image.

Image recognition method and system based on deep learning

An optical detection device includes a first linear light source, a second linear light source, an optical sensor array and a processor. The first linear light source is adapted to project a first long strip illumination beam onto the target container. The second linear light source is adapted to project a second long strip illumination beam onto the target container, and the second long strip illumination beam is crossed with the first long strip illumination beam. The optical sensor array is adapted to receive a first long strip detection beam and a second long strip detection beam reflected from the target container. The processor is electrically connected to the optical sensor array. The processor is adapted to analyze intensity distribution of the first long strip detection beam and the second long strip detection beam to acquire a relative distance between the optical sensor array and the target container.

Optical detection device

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.

Dirtiness level determining method and robot cleaner applying the dirtiness level determining method

Growing community of inventors

Hsin-Chu, Taiwan

Guo-Zhen Wang