Abstract: A waterproof fastener chain includes: a pair of fastener tapes made of polyester resin adjacent to each other at a given space between each side edge thereof, rows of elements respectively attached onto a main surface of the side edge of each of the fastener tapes, and waterproof coated films made of polyester resin respectively formed on a main surface of each of the fastener tapes. An outer surface of each of the waterproof coated films is flat at least at a position where a slider is to pass over, each of the waterproof coated films penetrates into irregularities on the main surface of each of the fastener tapes, a penetration depth of the waterproof coated films into a gap caused by the space of the pair of fastener tapes is not more than thickness of the fastener tapes.

Abstract: A waterproof fastener chain includes: a pair of fastener tapes made of polyester resin adjacent to each other at a given space between each side edge thereof, rows of elements respectively attached onto a main surface of the side edge of each of the fastener tapes, and waterproof coated films made of polyester resin respectively formed on a main surface of each of the fastener tapes. An outer surface of each of the waterproof coated films is flat at least at a position where a slider is to pass over, each of the waterproof coated films penetrates into irregularities on the main surface of each of the fastener tapes, a penetration depth of the waterproof coated films into a gap caused by the space of the pair of fastener tapes is not more than thickness of the fastener tapes.

Abstract: Disclosed is a method for accurately and efficiently detecting a modality of input data, including the steps of projecting the input data into a plurality of projection data using each of a plurality of transformation matrix groups U1·(?12U2T), generating a plurality of inverse projection data by performing inverse projection of the transformation matrix groups on the plurality of generated projection data, calculating a correlation between the input data and the generated inverse projection data with respect to each transformation matrix group U1·(?12U2T), and identifying a modality represented by a transformation matrix group having a highest calculated correlation as the modality of the input data.

Abstract: An image compression apparatus capable of compressing an input image that includes a predetermined target object at a high compression ratio while allowing high quality image restoration. In the apparatus, the input image is reduced and compressed. A region of interest corresponding to a predetermined target object is set in the input image. A partial area image of an expanded image of the compressed reduced image corresponding to the region of interest is converted to a high resolution image by applying a prediction process that uses a learning result obtained by learning the predetermined object in advance. With respect to the region of interest portion, a differential image between the image converted to the high resolution and the input image is generated and encoded. Reduced image compression data and differential image encoded data are outputted.

Abstract: To acquire a high-resolution frame from a plurality of frames sampled from a video image, it is necessary to obtain a high-resolution frame with reduced picture quality degradation regardless of motion of a subject included in the frame. Because of this, between a plurality of contiguous frames FrN and FrN+1, there is estimated a correspondent relationship. Based on the correspondent relationship, the frames FrN+1 and FrN are interposed to obtain first and second interpolated frames FrH1 and FrH2. Based on the correspondent relationship, the coordinates of the frame FrN+1 are transformed, and from a correlation value with the frame FrN, there is obtained a weighting coefficient ?(x°, y°) that makes the weight of the first interpolated frame FrH1 greater as a correlation becomes greater. With the weighting coefficient, the first and second interpolated frames are weighted and added to acquire a synthesized frame FrG.

Abstract: When obtaining a final result from a discriminator group arranged in a predetermined order, an evaluation value obtaining unit successively evaluates each discriminator from a first discriminator and if it is determined that a discrimination result represented by an overall evaluation value obtained by evaluating the first to Ith discriminators remains unchanged even if evaluation values of I+1th and subsequent discriminators are added to the overall evaluation value, a discrimination result determination unit instructs the evaluation value obtaining unit to terminate the evaluation of the I+1th and subsequent discriminators, and determines the discrimination result according to the overall evaluation value obtained by evaluating the first to Ith discriminators as a final result.

Abstract: When NN pairs of sample data are inputted, pre-processing and area division processing are performed by a pre-processing means and area division means respectively. Thereafter, when number of classes NP is inputted to projection matrix generation means based on the NN pairs of sample data, clustering in which NN pairs of sample data are classified into NP classes. Then, representative sample data representing each of classes (NP classes) are selected from NN pairs of sample data as the learning data. Then, based on the nature of Formula (2), calculation means generates an inverse first projection matrix (ML)?1 using a plurality of low resolution sample images (pre-transformation sample data) of a plurality of pairs of representative sample data and a second projection matrix MH using a plurality of high resolution sample images (post-transformation sample data). Thereafter, a transformation matrix {MH·(ML)?1} is generated by transformation matrix generation means.

Abstract: An eigenprojection matrix (#14) is generated by a projection computation (#12) using a local relationship from a studying image group (#10) including a pair of a high quality image and a low quality image to create a projection core tensor (#16) defining a correspondence between the low quality image and an intermediate eigenspace and a correspondence between the high quality image and the intermediate eigenspace. A first sub-core tensor is created (#24) from the projection core tensor based on a first setting, and an inputted low quality image (#20) is projected (#30) based on the eigenprojection matrix and the first sub-core tensor to calculate a coefficient vector in the intermediate eigenspace. The coefficient vector is projected (#34) based on a second sub-core tensor (#26) created by a second setting from the projection core tensor and based on the eigenprojection matrix to obtain a high quality image (#36).

Abstract: An image processing apparatus includes: an image obtaining section obtaining an input image; a first image processing section generating a predetermined quality image resulting from rendering the input image in high image quality using a predetermined image processing parameter; a display section displaying the predetermined quality image; a characteristic region identifying section identifying a plurality of characteristic regions in the input image; a parameter determining section determining, respectively for the plurality of characteristic regions, image processing parameters for rendering images of the plurality of characteristic regions, in higher image quality; a second image processing section generating a plurality of high quality characteristic-region images respectively of the plurality of characteristic regions, using the image processing parameters determined by the parameter determining section; and a display control section replacing the plurality of characteristic regions in the predetermined

Abstract: In an image processing device and method, program, and recording medium of the present invention, high frequency components of a low quality image and a high quality image included in a studying image set are extracted, and an eigenprojection matrix and a projection core tensor of the high frequency components are generated in a studying step. In a restoration step, a first sub-core tensor and a second sub-core tensor are generated based on the eigenprojection matrix and the projection core tensor of the high frequency components, and a tensor projection process is applied to the high frequency components of an input image to generate a high quality image of the high frequency components. The high quality image of the high frequency components is added to an enlarged image obtained by enlarging the input image to the same size as an output image.

Abstract: A tentative eigenprojection matrix (#12-a) is provisionally generated from a studying image group (#10) including a pair of a high quality image and a low quality image, and a tentative projection core tensor (#12-b) defining a correspondence between the low quality image and an intermediate eigenspace and a correspondence between the high quality image and the intermediate eigenspace is created. A first sub-core tensor is created from the tentative projection core tensor based on a first setting (#12-c), and the studying image group is projected based on the tentative eigenprojection matrix and the first sub-core tensor (#15-a) to calculate an intermediate eigenspace coefficient vector (#15-b).

Abstract: The present invention determines the adopting ratio (weight coefficient) between the high image quality processing using the tensor projection method and the high image quality processing using another method according to the degree of deviation of the input condition of the input image, and combines these processes as appropriate. This allows a satisfactory reconstruction image to be acquired even in a case of deviation from the input condition, and avoids deterioration of the high quality image due to deterioration of the reconstruction image by the projective operation.

Abstract: An image processing apparatus includes an encoding manner storing section that stores encoding manners in association with quantities of characteristics of objects, a characteristic region detecting section that detects a plurality of characteristic regions from an image, and a compressing section that compresses the images of the plurality of characteristic regions by encoding manners stored in the encoding manner storing section in association with the quantities of characteristics of objects included in the plurality of characteristic regions respectively.

Abstract: Provided is an image processing apparatus, including a characteristic region detecting section that detects a characteristic region from an input image; an image generating section that generates, from the input image, a low-quality image, which is of lower quality than the input image, and a characteristic region image, which is of higher quality than the low-quality image at least at the characteristic region; a difference processing section that generates a characteristic region difference image indicating a difference between an image of the characteristic region in the characteristic region image and an image of the characteristic region in the low-quality image; and an encoding section that encodes the characteristic region difference image and the low-quality image.

Abstract: The present invention provides a video in which a subject image looks clear while reducing the amount of transmitted data. An image capturing apparatus includes: an image capturing section that successively captures a plurality of images under a plurality of image capturing conditions different from each other; an image generating section that generates an output image by overlapping the plurality of captured images captured under the plurality of image capturing conditions; and an output section that outputs the output image generated by the image generating section. The image capturing section may successively capture the plurality of images by means of exposure in different exposure time lengths from each other. The image capturing section may successively capture the plurality of images also by means of exposure in different aperture openings from each other.

Abstract: In an aspect of an image processing technique according to the present invention, a high-frequency component is extracted from a low-resolution image z which is a restoration target, and a high-frequency image z? is generated (#20). Interpolation filter coefficients A?i, B?i and ?i and a representative high-frequency image z?i are set (#22), a Gaussian mixture model represented by x=?{((A?i×z?)+B?i)×wi((z?i?z?), ?i)} is assumed and a filtering process is applied to the high-frequency image z? (#24). On the other hand, an enlargement process is applied to a low-frequency component and a medium-frequency component of the low-resolution image z (#26), a processing result of the filtering process and a processing result of the enlargement process are added (#28), and a high-resolution image is restored.

Abstract: An examinee is subjected to an image or a sound suitable for the examinee's overcoming his worries in accordance with change in a physical state of the examinee.

Abstract: An image processing system providing a monitor image in which an image of a characteristic region is easily viewed. The image processing system includes an image obtaining section that obtains a moving image; a characteristic region information obtaining section that obtains information indicating positions of characteristic regions in a plurality of moving image constituting images included in the moving image; and an image generating section that generates display images having substantially the same size as each other, by reducing or enlarging each of images of the characteristic regions included in the plurality of moving image constituting images, based on the positions indicated by the information obtained by the characteristic region information obtaining section.

Abstract: An image processing system capable of reducing an operation time required to generate a high image quality image, includes an image obtaining section that obtains an input image having been captured; a characteristic region information obtaining section that obtains information indicating a characteristic region in the input image; a model storage section that stores a model representing an object by a character parameter; an image generating section that converts an image of an object included in the characteristic region in the input image into a high image quality image having an image quality higher than an image quality of the input image, by adapting the image of the object included in the characteristic region in the input image to the model; and an output section that outputs an image including the high image quality image and an image other than the characteristic region.

Abstract: When trimming is performed on a photograph image obtained by a photography apparatus, a plurality of trimming range candidates is set by analyzing the photograph image. A judgment is made as to whether the zoom magnification ratio of the photography apparatus during photography corresponds to a predetermined limit, the limit being a maximum zoom magnification ratio or a minimum zoom magnification ratio that can be set by the photography apparatus. A trimming range is set by selecting one of the plurality of trimming range candidates. If the zoom magnification ratio is judged to be a magnification ratio corresponding to the predetermined limit, a trimming range candidate that has a smaller or larger range than that of a trimming range candidate selected if the zoom magnification ratio is judged to be a magnification ratio that does not correspond to the predetermined limit is selected as the trimming range.