2399 results about "Region detection" patented technology

TV white space spectrum sensors and methods for detecting and managing the white space are provided. The sensor is provided with a spectrum detector/analyzer, which senses and analizes the wireless signals present in a spectrum of interest, identifies white space, and assigns the white space to secondary services. For reducing the white space detection time, the sensor uses a group detection method whereby multiple channels are sensed simultaneously. For reducing the sensor cost, the dynamic range of the sensor is reduced by operating the sensor in saturation for signals with the energy higher than a threshold. The sensor is also provided with a spectrum manager/planner capable of understanding a plurality of air interface standards, reserving and providing the right amount of white space spectrum to each application, based on the respective standard requirements. The particular architectures used by the sensor result in an affordable addition to any wireless device.

To provide a region detecting method capable of setting a proper threshold independently of a photographing condition and moreover, quickly and accurately detecting a specific region, which uses an image data storing section 10 for storing a sample image 12 and a purposed image 11, a first computing means 1 for obtaining the extraction-region-identifying threshold data for a plurality of sample images including a common extraction region but having average color values different from each other in accordance with a genetic algorithm and generating a threshold table 8 for the average color values, a second computing means 2 for adaptively computing the extraction-region-identifying threshold data for the purposed image 11 in accordance with the average color value of the purposed image and the threshold table 8, and a third computing means 3 for detecting an extraction region in accordance with the threshold data computed by the second computing means 12.

Systems and methods for foreground analysis in real-time video include background subtraction and foreground detection, shadow removal, quick lighting change adaptation, static foreground region detection, foreground fragment reduction, and frame level change detection. Processes include background image extraction and foreground detection, integrating texture information of the background image and a current frame to remove false positive foreground areas resulting from lighting changes, integrating pixel intensity information by determining a cross-correlation of intensities between a current frame and the background image for each pixel in a foreground mask to remove image shadows. Static foreground region detection and fragment reduction are also included.

An image processing device includes a subject region detector that detects a subject region from an input image; a cutting unit that cuts an image of the subject region from the input image; a priority calculator that calculates a priority of each of predetermined regions on a boundary with respect to the subject region, for the input image; a retrieval unit that retrieves a region similar to an image of a predetermined region with a top priority from among the priorities, from the input image after the image of the subject region is cut; a recovery unit that recovers the subject region by copying an image of an adjacent region that is adjacent to the region similar to the predetermined region retrieved by the retrieval unit and includes a region corresponding to a region cut as the subject region, and by pasting the image obtained by copying onto the region that is adjacent to the predetermined region with the top priority and cut as the subject region; and a composition unit that combines the image of the subject region cut by the cutting unit with the image with the subject region recovered by the recovery unit.

In the invention, a particular-region such as red-eye region of a photographed image is detected, the image including a person as an object. At first a particular region candidate satisfying detection conditions for the particular region candidate is detected from the image. Then, a face region of the person satisfying detection conditions for the face region of the person is detected and the particular region candidate is specified as a particular region to be detected, in a condition that the particular region candidate is included in the detected face region. On the other hand, the image is divided into first and second regions at least before the detecting of the face region of the person. The detection conditions used for the detection for the particular region candidate or the detection for the face region of the person are changed between the first region and the second region of the image.

The invention discloses an improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM (KS-weighting matching region)). The improvement is reflected as follows: 1) confirming a candidate region by utilizing Kalman filtering; 2) fixing a camera or not by adopting different pedestrian detecting strategies; 3) proposing a pedestrian detecting method of an HLS (hue, lightness and saturation) model with multi-characteristic fusion; and 4) dividing pedestrians based on CA obvious region detection of context sensing. According to the invention, pedestrians can be recognized accurately under complex occasions of blur details, complex backgrounds, noise influences and the like. And the improved weighting region matching high-altitude video pedestrian recognizing method (KS-WRM) provided by the invention can be used for pedestrian detection and recognition at places with high visitor flow rate, such as remote sensing satellite images, malls, subway stations, railway stations, airports, as well as intelligent traffic control, intelligent vehicle auxiliary driving, pedestrian flow rate statistics and analysis places.

The method and apparatus for detecting particular regions detect one or more particular region candidates in a first image, perform face detection in a region including at least one of the thus detected particular region candidates by using a second image having a scene as same as the first image in which the particular region candidates are detected, but being different in resolution from the first image, and specify as a particular region of a detection target a particular region candidate that is included in the region where a face can be detected. The program for detecting particular regions causes a computer to execute the method.

The particular region detecting method and apparatus detect particular region candidates in an image, then perform face detection in a region including one of the detected particular region candidates and specify as a particular region of a detection target the one candidate included in the region where a face can be detected. In the method and apparatus, detection conditions is changed for at least one of the candidate detection and the face detection between main and non-main portion regions of the image, face information regarding the face detected in the region is stored and the face detection corresponding to a particular region candidate to be next subjected to the face detection is performed using the thus stored face information. The program is caused a computer to execute the method.

Methods and apparatus for preventing fluctuations in ambient light from affecting the optical input mechanism of a liquid crystal display device. In one embodiment, an independent light source is adapted to generate electromagnetic signals through the cover glass of the display device. When the user's finger is proximate to a certain region of the touch panel, the electromagnetic signals reflect off of the user's finger and back through the cover glass. One or more photosensors monitoring the presence of these reflected signals service the various regions on the touch panel where input may be detected. Thus, when the reflected signals are detected at a certain region, the user's finger may be assumed to be present.

The invention relates to the technical field of man-machine interaction and provides a man-machine interaction method based on sight judgment, to realize the operation on an electronic device by a user. The method comprises the following steps of: obtaining a facial image through a camera, carrying out human eye area detection on the image, and positioning a pupil center according to the detected human eye area; calculating a corresponding relationship between an image coordinate and an electronic device screen coordinate system; tracking the position of the pupil center, and calculating a view point coordinate of the human eye on an electronic device screen according to the corresponding relationship; and detecting an eye blinking action or an eye closure action, and issuing corresponding control orders to the electronic device according to the detected eye blinking action or the eye closure action. The invention further provides a man-machine interaction system based on sight judgment. With the adoption of the man-machine interaction method, the stable sight focus judgment on the electronic device is realized through the camera, and control orders are issued through eye blinking or eye closure, so that the operation on the electronic device by the user becomes simple and convenient.

The present invention provides systems and methods for non-destructively detecting material abnormalities beneath a coated surface. A terahertz (THz) illumination unit illuminates an area of the coated surface. A detection unit detects light reflected from the illuminated area of the coated surface, and a processing unit images the illuminated area of the coated surface from optical characteristics received from the detection unit.

A ringing area detector classifies the input image into two regions: a mosquito noise region (i.e. filtering region) and a non-mosquito noise region (i.e. non-filtering region), and uses this classification information to adaptively remove the mosquito noise in a mosquito noise reduction system. The mosquito noise reduction system includes a ringing area detector, a local noise power estimator, a smoothing filter, and a mixer. The ringing area detector includes an edge detector, a near edge detector, a texture detector, and a filtering region decision block. The ringing detection block detects the ringing area where the smoothing filter is to be applied. The local noise power estimator controls the filter strength of the smoothing filter. The smoothing filter smoothes the input image. The mixer mixes the smoothed image and the original image properly based on the region information from the ringing area detection block.

In a method of high spatial resolution imaging a structure of a sample, the structure is marked with a substance. The substance is selected from a group of substances which are capable of being repeatedly transferred out of a first state having first optical properties into a second state having second optical properties by means of an optical switch over signal, and which are capable of returning out of the second state into the first state, the two states differing with regard to at least one criteria. Within areas of the sample the sample is transferred into the second state by means of the optical switch over signal with which at least one spatially limited area of the sample is purposefully omitted. An optical measurement signal is detected, which is associated with the substance in the first state and which comes out of a detection area including both the area purposefully omitted with the switch over signal and areas in which the substance has been transferred into to second state.

A face portion detection device, a behavior content classification device, a speech content classification device, a car navigation system, a face direction classification device, a face portion detection device control program, a behavior content classification device control program, a face portion detection device control method, and a behavior content classification device control method are provided for appropriately classifying a behavior content of the object person from a captured image including the face of the object person. A speech section detection device 1 includes an image capturing unit 10, a data storage unit 11, an image processing unit 12, a lip region detection unit 13, feature extraction unit 14, and a speech section detection unit 15. The lip region detection unit 13 uses a dedicated SVM to detect a lip region from a captured image, and the speech section detection unit 15 uses features of an image of a detected lip region and a dedicated HMM to detect a speech section.

An exposure value is determined based on a face region, with high accuracy and with less effect of a background region or density contrast caused by shadow. For this purpose, a face detection unit detects a face region from a face candidate region in a through image detected by a face candidate detection unit, by fitting to the face candidate region a mathematical model generated by a method of AAM using a plurality of sample images representing human faces. An exposure value determination unit then determines an exposure value for photography, based on the face region.

An RGB-Z sensor is implementable on a single IC chip. A beam splitter such as a hot mirror receives and separates incoming first and second spectral band optical energy from a target object into preferably RGB image components and preferably NIR Z components. The RGB image and Z components are detected by respective RGB and NIR pixel detector array regions, which output respective image data and Z data. The pixel size and array resolutions of these regions need not be equal, and both array regions may be formed on a common IC chip. A display using the image data can be augmented with Z data to help recognize a target object. The resultant structure combines optical efficiency of beam splitting with the simplicity of a single IC chip implementation. A method of using the single chip red, green, blue, distance (RGB-Z) sensor is also disclosed.

An image processing apparatus which processes an input image to detect a specified object of interest that is recorded in the input image is provided. The apparatus has a detection unit and a position determining unit. The detection unit has a plurality of identifying subunits each of which identifies an object from the input image under a different condition. The detection unit detects a region of the identified object. The position determining unit calculates the position coordinates of the object of interest in the input image from the region of the identified object. The detection unit performs the identification and the detection repeatedly and the detection unit performs the identification and the detection by using a detected region of an identified object in the previous identification. The detection unit detects the specified object of interest using the repeatedly detected regions.

The invention relates to the technical field of stereo vision, in particular to a stereo matching method. The method solves the problem that the accuracy of disparity correction optimization of the existing stereo matching method is insufficient. The stereo matching method based on disparity map pixel classification correction optimization comprises the following steps that (I) cost aggregation is conducted by taking a left view and a right view as references and based on a method combining a gray scale difference with a gradient, and a left disparity map and a right disparity map are obtained and subjected to left and right consistency detection to generate an initial reliable disparity map; (II) correlation credibility detection and weak texture area detection are conducted, and a pixel is classified into stable matching pixel points, unstable matching pixel points, occlusion area pixel points and weak texture area pixel points; (III) the unstable matching points are corrected by an adaptive weight algorithm based on improvement, and the occlusion area points and the weak texture area points are corrected by a mismatching pixel correction method; and (IV) the corrected disparity maps are optimized by an algorithm based on division, and dense disparity maps are obtained.

A particular-region such as red-eye region of a person in an image is detected at a high speed by a particular-region detection apparatus, as follows. At first, a region of the image satisfying detection conditions for particular region candidates is detected as a particular region candidate. Next, a face region of a first person is detected and the particular region candidate is specified as a particular region to be detected on condition that the particular region candidate is included in the detected face region. Then, face information regarding a face of the first person obtained when the face region is detected is stored. When a face region of a second person is further detected in the image or other image after storing of the face information, the face information is accessed and recalled and the face region of the second person is detected by using the face information as a face detection condition.

A sample image is filtered through a circumferential filter 28, an image feature amount is learned in a discrimination section 30, an image G to be searched is filtered through the circumferential filter 28 to detect a rotation invariant image feature amount for each filtered area, and each detected image feature amount is inputted into the discrimination section 30. Thereby, it is discriminated whether or not a filtering area is considered to be face image at high speed. And the dimensional number of image feature amounts is greatly reduced, so that not only the discrimination work but also the learning time of the sample image are greatly reduced.

A video surveillance equipment for detecting a change of an object in a monitoring area based on input images captured by an image capturing device, the equipment comprising:

• • an area detection apparatus for detecting a second image area being stationary for a predetermined time in a first image area which is an area differing between a reference image used as a reference in image processing and the input images;
  • a memory apparatus for storing image of the detected second image area; and
  • an image comparison apparatus for performing comparison processing a plurality of times between the stored image and image in the second image area included in the input images.

Photographed images from a front camera and a side camera respectively installed at the front and left side of a vehicle are respectively converted into bird's-eye view images, and a synthetic bird's-eye view image is displayed which is obtained by synthesizing the bird's-eye view images. Based on a difference image between the front and side cameras, a difference region where a solid object is drawn is detected from a common region where the both bird's-eye view images overlap. Then, based on position of each pixel forming the difference region, it is evaluated which of the front and side cameras captures the solid object better, and an image of the common region in the synthetic bird's-eye view image is formed based on the image obtained from one of the cameras.

A drivable region detection method, a drivable region detection device, and electronic equipment are disclosed. The method comprises the steps of acquiring image information of a driving environment collected by an imaging device, detecting the environment border of the driving environment according to the image information, detecting an obstacle in the driving environment, and determining a drivable region in the driving environment according to the environment border and the obstacle. Therefore, a drivable region in a driving environment can be detected reliably.