Nec Corporation

Banyu Pharmaceutical Co. Ltd

Samsung Electronics Co., Ltd.

Toshio Kamei

Masahiro Hayashi

Yoshimi Tsuchiya

Teruyuki Higuchi

Yoshikazu Iwasawa

Takashi Nomoto

Toshihiko Satoh

Mitsuru Ohkubo

Yoichi Nakamura

Yasufumi Nagata

Hitoshi Masaki

Yumiko Sakuma

Hyun-woo Kim

Tae-kyun Kim

Morihiro Mitsuya

Katsumasa Nonoshita

Won-Jun Hwang

Seok-cheol Kee

Yoshiaki Iida

Masaaki Hosoi

Takeo Tamura

Yoshio Sawasaki

Tomoomi Iwata

Hiroshi Takezawa

Masahiro Horie

The present invention is a biometric authentication apparatus comprising, a fingertip sensor mounted on a tip placement surface of a tip placement section for placing a tip of a finger cushion said fingertip sensor detecting displacement of an arrangement position of a finger on the tip placement surface of the tip placement section, wherein the biometric authentication apparatus detects the displacement of a position of the tip of the finger cushion.

Biometric authentication apparatus and biometric authentication method

A biometric authentication apparatus of the present invention comprises: a finger-tip placing detecting means for detecting placing of a finger-tip onto a finger-tip placing section; a finger-base-part placing detecting means for detecting placing of a finger-base part onto a finger-base-part placing section; and a guidance means for conducting guidance of whether or not the finger-tip or the finger-base part has been placed, on the basis of the results of the detections conducted by the finger-tip placing detecting means and the finger-base-part placing detecting means.

[Problem] To separate biological patterns more efficiently and effectively. [Solution] An image processing apparatus according to the present invention is characterized by comprising: an image obtaining means for obtaining an image in which a first biological pattern and a second biological pattern having different textures are superimposed; a normalizing means for normalizing density of the image on the basis of an average and a standard deviation of pixel values inside a local region in the image using a parameter in accordance with difference in texture between the first biological pattern and the second biological pattern to thereby separate the first biological pattern and the second biological pattern in the image; and a pattern collating means for collating a known pattern for collation with each of the first biological pattern and the second biological pattern separated by the normalizing means.

Image processing apparatus, image processing method, and image processing program

The similarity calculation device is provided with a displacement vector estimation unitfor estimating a displacement vector between a first local region set in a first image, and a second local region which is most similar to the first local region in a second image, a geometric transformation parameter estimation unitfor estimating a geometric transformation parameter which geometrically transforms the first image into the second image, a displacement vector correction unitfor correcting the displacement vector based on the geometric transformation parameter, a scoring unitfor scoring the displacement vector, corrected by the displacement vector correction unit, in a two-dimensional space and creating a scored image, a peak detection unitfor detecting a peak in the scored image, and a similarity calculation unitfor calculating a similarity of the first image and the second image according to a size of the peak.

Similarity calculation device, similarity calculation method, and program

Provided are a collating device, a processing method and a collation program, in which a reference line is extracted from an image and each partial image is moved in a manner that the reference line becomes a predetermined one thereby to correct the image, and in which the corrected image is collated so that an authentication result can be obtained for a short time period without any rotating operation. At first, a reference line extracting unit extracts the center line or the contour line of the image as the reference line. Next, an image correcting unit moves each partial image in parallel thereby to correct the image so that the reference line obtained by the reference line extracting unit becomes a predetermined one. Moreover, an image collating unit collates the image corrected by the image correcting unit and a predetermined image to acquire an authentication result.

Collating device, collating method, and program

A 2-dimensional pattern matching method contains a process of extracting a query feature data by projecting a vector representation of either of a query 2-dimensional pattern and a transformed query 2-dimensional pattern which is generated by transforming the query 2-dimensional pattern, to a feature space. An enrollment feature data as previously enrolled and a query feature data are inversely projected to the 2-dimensional pattern representation space which has the dimension of the vector representation and the similarity is calculated. The data size of a feature amount is small and a matching technique robust to the positional displacement and the image distortion is provided.

Matching method for two-dimensional pattern, feature extracting method, apparatus used for the methods, and programs

Provided is a biometric authentication device that can enhance usability, suppress deterioration of authentication accuracy due to ambient noise, and increase tolerance to wiretapping. A biometric authentication device generates a signal pattern toward a living body by using a signal pattern generating means 11, and transmits the signal pattern to the living body in accordance with the signal pattern by a signal transmitting means 12. Further, the device receives a response signal transmitted through the living body by a signal receiving means 13. The device then calculates transfer feature in accordance with the signal pattern and the response signal by a transfer feature calculating means 14. Further, the device extracts and collates a feature amount in accordance with the transfer features.

Biometric authentication device, biometric authentication method, and storage medium

An input pattern feature amount is decomposed into element vectors. For each of the feature vectors, a discriminant matrix obtained by discriminant analysis is prepared in advance. Each of the feature vectors is projected into a discriminant space defined by the discriminant matrix and the dimensions are compressed. According to the feature vector obtained, projection is performed again by the discriminant matrix to calculate the feature vector, thereby suppressing reduction of the feature amount effective for the discrimination and performing effective feature extraction.

Pattern feature extraction via fourier amplitudes of a block image

A face feature is extracted by a face feature extracting unit, a confidence index is extracted by a confidence index extracting unit, and then, they are outputted as a face meta-data. At a time of matching, by using the confidence index of the face meta-data, a distribution estimating unit estimates the data of a parameter and the like with regard to a posterior distribution when the confidence index is obtained. A distance calculating unit calculates a similarity between feature values. Consequently, the precision of face verification can be improved, thereby carrying out a practical face matching.

Face meta-data generation and face similarity calculation

A method and apparatus for extracting feature vectors for face recognition and retrieval are provided. An entire Fourier feature vector is generated for an entire face area of a normalized face image using first and second normalized vectors, and a central Fourier feature vector is generated for a central face area of the normalized face image using third and fourth normalized vectors. An entire intensity feature vector is generated for the entire face area, and a local intensity feature vector is generated for a predetermined number of face component-wise areas. An entire composite feature vector is generated by coupling the first and second normalized vectors and the entire intensity feature, and a central composite feature vector is generated by coupling the third and fourth normalized vectors and the local intensity feature vectors.

Method and apparatus for extracting feature vector used for face recognition and retrieval

A moving object is detected by subtraction between successive frames produced by a video camera and a position and a size of the moving object are determined. Preceding and succeeding frames produced by the video camera are stored into respective memories and the panning, tilting and zooming functions of the video camera are controlled according to the determined position and size of the moving object. A motion compensation is performed on the preceding frame to compensate for a motion of background image caused by a tracking movement of the camera so that coordinates of the motion-compensated frame are transformed to coordinates of the succeeding frame. An image difference between the motion-compensated frame and the succeeding frame is extracted as a moving object and a position and a size of the extracted image are determined, with which the video camera is adaptively controlled.

Method and system for tracking a fast moving object

For providing an efficient image pattern matching system, an image feature extractor (,) of the invention comprises a feature vector extraction means (,) for extracting a feature vector from the pattern image, a quality index extraction means (,) for extracting quality index information of the pattern image, an error distribution information storing means (,) wherein error distribution information representing correlation between error distribution of the feature vector and the quality index information is prepared, and a confidence attribution means (,) for obtaining confidence estimation information referring to the error distribution information retrieved with the quality index information. The image feature analyzer (,) prepares the errors distribution information. An image feature matching system collates feature information of an image pattern extracted by the image feature extractor (,) by comparing it to registered feature information.

Image feature extractor, an image feature analyzer and an image matching system

For providing an efficient image pattern matching system, an image feature extractor (11) of the invention comprises a feature vector extraction means (101) for extracting a feature vector from the pattern image, a quality index extraction means (106) for extracting quality index information of the pattern image, an error distribution information storing means (105) wherein error distribution information representing correlation between error distribution of the feature vector and the quality index information is prepared, and a confidence attribution means (107) for obtaining confidence estimation information referring to the error distribution information retrieved with the quality index information. The image feature analyzer (51) prepares the error distribution information. An image feature matching system collates feature information of an image pattern extracted by the image feature extractor (11) by comparing it to registered feature information.

Image feature extractor and an image feature analyzer

A skin pattern image is filtered by convolution calculation on a real plane or product calculation on a Fourier transformed plane with each of two-dimensional filters prepared according to kinds of features to be extracted of the skin pattern image. Image intensity of each subregion of each filtered data is calculated. Feature of each subregion is represented by a feature parameter corresponding to a filter that gives a highest value of the image intensity of the subregion. An initial pattern of features thus obtained is smoothed to minimize an evaluation function. A filtered skin pattern image having pixel values of each subregion smoothed by a set of filters prepared for extracting a kind of features is further filtered by another set of filters for extracting another kind of features.

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Tokyo, Japan

Toshio Kamei