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1039 results about "Image type" patented technology

Perceptual similarity image retrieval

A system and method indexes an image database by partitioning an image thereof into a plurality of cells, combining the cells into intervals and then spots according to perceptual criteria, and generating a set of spot descriptors that characterize the perceptual features of the spots, such as their shape, color and relative position within the image. The shape preferably is a derivative of the coefficients of a Discrete Fourier Transform (DFT) of the perimeter trace of the spot. The set of spot descriptors forms as an index entry for the spot. This process repeated for the various images of the database. To search the index, a key comprising a set of spot descriptors for a query image is generated and compared according to a perceptual similarity metric to the entries of the index. The metric determines the perceptual similarity that the features of the query image match those of the indexed image. The search results are presented as a scored list of the indexed images. A wide variety of image types can be indexed and searched, including: bi-tonal, gray-scale, color, “real scene” originated, and artificially generated images. Continuous-tone “real scene” images such as digitized still pictures and video frames are of primary interest. There are stand alone and networked embodiments. A hybrid embodiment generates keys locally and performs image and index storage and perceptual comparison on a network or web server.
Owner:MIND FUSION LLC

Perceptual similarity image retrieval

InactiveUS20030231806A1High degree of successInsensitive to irrelevant detailData processing applicationsDigital data information retrievalWeb serviceContinuous tone
A system and method indexes an image database by partitioning an image thereof into a plurality of cells, combining the cells into intervals and then spots according to perceptual criteria, and generating a set of spot descriptors that characterize the perceptual features of the spots, such as their shape, color and relative position within the image. The shape preferably is a derivative of the coefficients of a Discrete Fourier Transform (DFT) of the perimeter trace of the spot. The set of spot descriptors forms as an index entry for the spot. This process repeated for the various images of the database. To search the index, a key comprising a set of spot descriptors for a query image is generated and compared according to a perceptual similarity metric to the entries of the index. The metric determines the perceptual similarity that the features of the query image match those of the indexed image. The search results are presented as a scored list of the indexed images. A wide variety of image types can be indexed and searched, including: bi-tonal, gray-scale, color, "real scene" originated, and artificially generated images. Continuous-tone "real scene" images such as digitized still pictures and video frames are of primary interest. There are stand alone and networked embodiments. A hybrid embodiment generates keys locally and performs image and index storage and perceptual comparison on a network or web server.
Owner:MIND FUSION LLC

Image type fire flame identification method

The invention discloses an image type fire flame identification method. The method comprises the following steps of 1, image capturing; 2, image processing. The image processing comprises the steps of 201, image preprocessing; 202, fire identifying. The fire identifying comprises the steps that indentifying is conducted by the adoption of a prebuilt binary classification model, the binary classification model is a support vector machine model for classifying the flame situation and the non-flame situation, wherein the building process of the binary classification model comprises the steps of I, image information capturing;II, feature extracting; III, training sample acquiring; IV, binary classification model building; IV-1, kernel function selecting; IV-2, classification function determining, optimizing parameter C and parameter D by the adoption of the conjugate gradient method, converting the optimized parameter C and parameter D into gamma and sigma 2; V, binary classification model training. By means of the image type fire flame identification method, steps are simple, operation is simple and convenient, reliability is high, using effect is good, and the problems that reliability is lower, false or missing alarm rate is higher, using effect is poor and the like in an existing video fire detecting system under a complex environment are solved effectively.
Owner:东开数科(山东)产业园有限公司

Computer-implemented image acquisition system

An image acquisition system has a computer and one or more imaging devices coupled to the computer. Each imaging device has a device memory and is capable of capturing a digital image and storing the image in its memory. An image device manager is implemented in software on the computer to control operation of the imaging devices. The image device manager presents a user interface (UI) within the familiar graphical windowing environment. The UI has a context space that pertains to a particular imaging context (e.g., scanning, photography, and video). The UI also has a persistently-visible imaging menu positioned within the context space that lists options particular to the imaging context. For example, if the context space pertains to the digital camera context, the menu lists options to take a picture, store the image on the computer, send the image in an email, and so on. In the scanner context, the menu lists options to select an image type, preview an image, send the image to a particular destination, and scan the image. The image acquisition system also includes a set of application program interfaces (APIs) that expose image management functionality to applications. The APIs enable applications to manage loading and unloading of imaging devices, monitor device events, query device information properties, create device objects, capture images using the devices, and store or manipulate the images after their capture.
Owner:MICROSOFT TECH LICENSING LLC

Image type automatic analysis method for mesh adhesion rice corn

InactiveCN101281112AOvercoming problems that are difficult to analyze automaticallyRemove the restriction of non-stick placementImage analysisMaterial analysis by optical meansAutomatic segmentationSplit lines
The invention discloses an image automatic analysis method for reticulate adhesion rice. The method firstly images rice under the grade of a reference backlight, and enables the reticulate adhesion rice to belong to the different local regions separately through an automatic segmentation. Secondly, the automatic segmentation includes that fat circular rice is carried on a distance transformation and a watershed transformation to be divided, as well as to use a circular template to get the concave angle point of long rice after the long rice is carried out watershed transformation, and the separation line can be determined and the wrong separation line can be removed according to the concave angle point. Different colors is using to color complete polished rice, broken rice and the rice whose length is in the critical region and to color background and chalkiness so as to figure out the grain number, the length, the width and the length to width ratio of each grain, finally, and the entire polished rice rate, the broken rice rate, the chalkiness degree and the chalkiness grain rate, and to form an analysis report. The invention overcomes the problem that the reticulate adhesion rice is difficult to be carried on automated analysis, and removes the limit of the request analysis sample is not in adhesion placing.
Owner:ZHEJIANG SCI-TECH UNIV
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