Kits, diagnostic systems and methods are provided, which measure the distribution of colors of skin features by comparison to calibrated colors which are co-imaged with the skin feature. The colors on the calibration template (calibrator) are selected to represent the expected range of feature colors under various illumination and capturing conditions. The calibrator may also comprise features with different forms and size for calibrating geometric parameters of the skin features in the captured images. Measurements may be enhanced by monitoring over time changes in the distribution of colors, by measuring two and three dimensional geometrical parameters of the skin feature and by associating the data with medical diagnostic parameters. Thus, simple means for skin diagnosis and monitoring are provided which simplify and improve current dermatologic diagnostic procedures.

In one embodiment of the present invention, a native resolution analyzer generates a log-magnitude spectrum that elucidates sampling operations that have been performed on a scene. In operation, the native resolution analyzer performs a transform operation of a color component associated with a frame included in the scene to generate a frame spectrum. The native resolution analyzer then normalizes the magnitudes associated with the frame spectrum and logarithmically scales the normalized magnitudes to create a log-magnitude frame spectrum. This two dimensional log-magnitude frame spectrum serves as a frequency signature for the frame. More specifically, patterns in the log-magnitude spectrum reflect re-sampling operations, such as a down-sampling and subsequent up-sampling, that may have been performed on the frame. By analyzing the log-magnitude spectrum, discrepancies between the display resolution of the scene and the lowest resolution with which the scene has been processed may be detected in an automated fashion.

An automatic generation system of a training image and a method thereof are provided. The disclosure generates a training image and records the target category and the target position. The disclosure adds the target image to the container image as a candidate image, calculates a reliability of the candidate image, and repeatedly executes the process until the reliability of the candidate image meets a threshold condition for generating the training image. The disclosure is able to generate the training images automatically, and the recognition difficulty of the training image is adjustable by the user, so as to be suitable for customized recognition training.

An automatic generation system of a training image and a method thereof are provided. The disclosure generates a training image and records the target category and the target position. The disclosure adds the target image to the container image as a candidate image, calculates a reliability of the candidate image, and repeatedly executes the process until the reliability of the candidate image meets a threshold condition for generating the training image. The disclosure is able to generate the training images automatically, and the recognition difficulty of the training image is adjustable by the user, so as to be suitable for customized recognition training.

A beverage dispenser includes a nozzle to dispense a beverage. The beverage dispenser further includes a camera to capture an image of the beverage as the beverage is dispensed from the nozzle. The camera has a field of view that includes the beverage. The beverage dispenser further includes a light source that illuminates the field of view of the camera. The beverage dispenser further includes a computer. The computer analyzes the image of the beverage and determines a characteristic of the beverage.

A beverage dispenser includes a nozzle to dispense a beverage. The beverage dispenser further includes a camera to capture an image of the beverage as the beverage is dispensed from the nozzle. The camera has a field of view that includes the beverage. The beverage dispenser further includes a light source that illuminates the field of view of the camera. The beverage dispenser further includes a computer. The computer analyzes the image of the beverage and determines a characteristic of the beverage.

A circuit device 100 includes an error detection circuit 110 and a processing circuit 120. The error detection circuit 110 obtains a glare index value, which is an index value indicating glare of a head-up display, based on image data IMD for head-up display. The error detection circuit 110 determines whether or not a glare index value has exceeded a first threshold value, and when the glare index value exceeds the first threshold value, detects occurrence of a first glare error. When occurrence of a first glare error is detected, the processing circuit 120 performs processing corresponding to the first glare error.

A circuit device 100 includes an error detection circuit 110 and a processing circuit 120. The error detection circuit 110 obtains a glare index value, which is an index value indicating glare of a head-up display, based on image data IMD for head-up display. The error detection circuit 110 determines whether or not a glare index value has exceeded a first threshold value, and when the glare index value exceeds the first threshold value, detects occurrence of a first glare error. When occurrence of a first glare error is detected, the processing circuit 120 performs processing corresponding to the first glare error.

A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.

A system and method of identifying objects is provided. In one aspect, the system and method includes a hand-held device with a display, camera and processor. As the camera captures images and displays them on the display, the processor compares the information retrieved in connection with one image with information retrieved in connection with subsequent images. The processor uses the result of such comparison to determine the object that is likely to be of greatest interest to the user. The display simultaneously displays the images the images as they are captured, the location of the object in an image, and information retrieved for the object.