Abstract: The present invention discloses a concrete test device and method based on a load-corrosion coupling action, relating to the technical field of corrosion experimental devices for concrete sewage pipelines. The device simulates a real environment of a sewage pipeline based on the load-corrosion coupling action, applies mechanical load and chemical corrosion effects to a concrete specimen simultaneously, and accelerates a corrosion effect on the concrete specimen by exposing the concrete specimen. According to the device, researches on mechanical properties of a concrete material under the load-corrosion coupling action are realized, and an assessment sample basis is provided for researches on aging characteristics of the concrete sewage pipelines. The present invention further discloses a concrete test method based on the aforementioned test device.

Abstract: The present invention discloses a concrete test device and method based on a load-corrosion coupling action, relating to the technical field of corrosion experimental devices for concrete sewage pipelines. The device simulates a real environment of a sewage pipeline based on the load-corrosion coupling action, applies mechanical load and chemical corrosion effects to a concrete specimen simultaneously, and accelerates a corrosion effect on the concrete specimen by exposing the concrete specimen. According to the device, researches on mechanical properties of a concrete material under the load-corrosion coupling action are realized, and an assessment sample basis is provided for researches on aging characteristics of the concrete sewage pipelines. The present invention further discloses a concrete test method based on the aforementioned test device.

Abstract: An image processing apparatus that performs individual optimum image processing on each of a portion of an image illuminated by a light source and a portion of the image shaded from the light source, an image pickup apparatus, an image processing method, and a computer program are provided.

Abstract: A night-scene light source detecting device includes a pixel value obtaining unit configured to obtain a pixel value of each pixel in an input image; a night-scene-feature extraction unit provided for extracting a zone area of a mean corrected-brightness value and a high corrected-brightness value of the input image as two night-scene features based on the pixel value of each pixel in the input image; a night-scene image detection unit provided for determining whether the input image is a night-scene image or not based on the two night-scene features; a specific color detection unit provided for detecting whether each pixel belongs to specific color or not; and a night-scene light source determining unit provided for determining whether the night-scene image is picked up under irradiation by the specific light sources in a night scene or not based on the result of the specific color detection.

Abstract: Disclosed is a sky detection system that detects sky in an image collection device. The system includes an image collection unit that collects information of a color image; a color-feature extraction unit that extracts a color feature of each pixel from the collected image; a distance measurement unit that measures a distance between each pixel of the collected image and a lens; a first classification unit that classifies each pixel of the collected image as either a sky pixel or a non-sky pixel based on the color feature; and a second classification unit that further classifies each pixel of the collected image as either the sky pixel or the non-sky pixel based on the distance and a result of the first classification unit.

Abstract: A device for detecting a shadow region in an image includes an imaging module generating a multi-channel image including brightness, red, green, and blue channels, a brightness correcting module correcting values of the brightness channel based on imaging parameters and outputting a corrected multi-channel image, a scene classifying module determining to carry out a shadow detection on the corrected multi-channel image, a shadow detecting module classifying pixels of the corrected multi-channel image into a shadow or non-shadow pixel, and generating a shadow classification mark matrix having pixels having a shadow classification mark value corresponding to the classification, a region segmentation module segmenting the multi-channel image into regions having pixels having similar color values, and generating a region mark matrix having pixels having a region mark value, and a post-processing module updating the shadow classification mark matrix based on the shadow classification mark matrix and region mark ma

Abstract: A night-scene light source detecting device includes a pixel value obtaining unit configured to obtain a pixel value of each pixel in an input image; a night-scene-feature extraction unit provided for extracting a zone area of a mean corrected-brightness value and a high corrected-brightness value of the input image as two night-scene features based on the pixel value of each pixel in the input image; a night-scene image detection unit provided for determining whether the input image is a night-scene image or not based on the two night-scene features; a specific color detection unit provided for detecting whether each pixel belongs to specific color or not; and a night-scene light source determining unit provided for determining whether the night-scene image is picked up under irradiation by the specific light sources in a night scene or not based on the result of the specific color detection.

Abstract: Disclosed are a system and a method for detecting a multi-view human face. The system comprises an input device configured to input image data; a hybrid classifier including a non-human-face rejection classifier configured to roughly detect non-human-face image data and plural angle tag classifiers configured to add an angle tag into the image data having a human face; and plural cascade angle classifiers. Each of the plural cascade angle classifiers corresponds to a human face angle. One of the plural cascade angle classifiers receives the image data with the angle tag output from the corresponding angle tag classifier, and further detects whether the received image data with the angle tag includes the human face.

Abstract: An image processing apparatus that performs individual optimum image processing on each of a portion of an image illuminated by a light source and a portion of the image shaded from the light source, an image pickup apparatus, an image processing method, and a computer program are provided.

Abstract: Disclosed are a backlight detection device and a backlight detection method. The device comprises a pixel value acquiring unit used to acquire a pixel value of each of pixels in an image; a focal position determination unit used to determine a focal position in the image; a subject area determination unit used to determine, based on the pixel values of the pixels in the image, a subject area starting from the focal position by using an area growth processing so as to divide the image into the subject area and a background area; a brightness difference calculation unit used to calculate a brightness difference between the subject area and the background area; and a backlight determination unit used to determine, based on the brightness difference, whether the image is in the backlight state so that the image in the backlight state can be detected.

Abstract: Disclosed are an apparatus and a method for determining a multi-view specific object. The apparatus comprises an input device for inputting image data; and cascade classifiers formed of stage classifiers corresponding to a same detection angle, the stage classifiers corresponding to different features. Each cascade classifier is for calculating a degree of confidence of the image data of a specific object corresponding to the detection angle based on the aspect of the corresponding feature, and determining whether the image data belongs to the specific object based on the degree of confidence. A self-adaptive posture prediction device is disposed between two stage classifiers in each cascade classifier, and is used to determine whether the image data enters the cascade classifiers corresponding to the detection angles and located after the self-adaptive posture prediction device.

Abstract: Disclosed is a sky detection system that detects sky in an image collection device. The system includes an image collection unit that collects information of a color image; a color-feature extraction unit that extracts a color feature of each pixel from the collected image; a distance measurement unit that measures a distance between each pixel of the collected image and a lens; a first classification unit that classifies each pixel of the collected image as either a sky pixel or a non-sky pixel based on the color feature; and a second classification unit that further classifies each pixel of the collected image as either the sky pixel or the non-sky pixel based on the distance and a result of the first classification unit.

Abstract: A device for detecting a shadow region in an image includes an imaging module generating a multi-channel image including brightness, red, green, and blue channels, a brightness correcting module correcting values of the brightness channel based on imaging parameters and outputting a corrected multi-channel image, a scene classifying module determining to carry out a shadow detection on the corrected multi-channel image, a shadow detecting module classifying pixels of the corrected multi-channel image into a shadow or non-shadow pixel, and generating a shadow classification mark matrix having pixels having a shadow classification mark value corresponding to the classification, a region segmentation module segmenting the multi-channel image into regions having pixels having similar color values, and generating a region mark matrix having pixels having a region mark value, and a post-processing module updating the shadow classification mark matrix based on the shadow classification mark matrix and region mark ma