Abstract: An adaptive touch panel system and an adaptive method thereof are provided. The adaptive touch panel system includes a touch panel and an environment sensing device. The touch panel includes a touch sensor and a control device. The touch sensor senses a touch event and correspondingly outputs touch raw data. The control device includes a plurality of setting modes. The plurality of setting modes include a general setting mode and at least one special setting mode. The environment sensing device senses a current operating environment of the touch panel and generates at least one environmental physical parameter. The control device is configured to correspondingly select one of the plurality of setting modes according to the at least one environmental physical parameter, set the touch sensor according to the selected setting mode, and analyze the touch raw data to generate touch data.

Abstract: An electronic apparatus, system, and method for providing body posture health information are provided. The method includes the steps of: calculating a posture data cluster based on signals detected by an inertial sensor disposed on a human body; comparing the posture data cluster with a plurality of preset posture data clusters individually to determine whether the posture data cluster matches one of the preset posture data clusters; if it matches one of the preset posture data clusters, generating a feedback message; calculating a plurality of muscle status indexes based on signals detected by electromyography sensors disposed on the human body; comparing the muscle status indexes with corresponding preset muscle status indexes individually to determine whether one of the muscle status indexes is abnormal; providing suggestion information in response to at least one of the muscle status indexes being abnormal; and displaying a multimedia corresponding to the suggestion information.

Abstract: A method includes providing a substrate including a first fin element and a second fin element extending from the substrate, and forming a first layer including a first material over the first and second fin elements, wherein the first layer includes a gap disposed between the first and second fin elements. An anneal process is performed to remove the gap in the first layer, wherein performing the anneal process includes adjusting an energy applied to the first layer during the anneal process. The gap is filled by a portion of the first material around the gap reaching a sub-melt temperature that is different from a melting point of the first material.

Abstract: In some implementations, an image recognition system is capable of using an iterative multi-stage image matching procedure to improve the accuracy and/or reliability of matching a search image with a small number of distinctive feature points to reference images. In the first stage, the system compares a search template for the search image to reference templates of each image within the set of reference images. The system determines a best-matched reference image from among the reference images of the set of reference images. In the second stage, the system compares the hybrid search template to one or more reference templates of reference images that is not the best-matched reference image. The comparison can be used to either compute match scores for reference images corresponding to the one or more reference templates.

Abstract: A combination includes a luggage piece having a booster seat removably mounted thereupon. The luggage includes a housing adapted to contain belongings, wheels for rolling movement, and a retractable luggage handle. The booster seat forms a seat having an upper surface adapted for the child to sit upon. First and second securing mechanisms enable the booster seat to be removably mounted on the luggage, until released by a release device.

Abstract: Some implementations of the systems and techniques described include a tattoo recognition system that is capable of improving the accuracy and efficiency associated with matching edge curves extracted from tattoo images, which are typically performed during a tattoo matching operation. The system can perform a matching operation in two stages—a feature extraction stage and a matching stage. In the first stage, the system extracts one or more edge curves from the tattoo image. In the second stage, the system performs matching using a two-step comparison that compares features of the extracted edge curves.

Abstract: Systems and methods may be used by an automatic fingerprint identification system to estimate patterns of a latent fingerprint. A latent fingerprint image, and a plurality of reference ridge flow maps may initially be obtained. Each reference ridge flow map may be associated with a particular fingerprint pattern. A latent ridge flow map for the obtained latent fingerprint image may be computed. One or more characteristics associated with the latent ridge flow map may be compared to one or more characteristics associated with each of the plurality of reference ridge flow maps. A similarity score between the latent ridge flow map and a particular reference ridge flow map may be computed for each of the plurality of reference ridge flow maps. One or more fingerprint patterns present within the latent fingerprint may then be determined and provided for output.

Abstract: In some implementations, systems and techniques are capable of performing a multi-stage tattoo matching operation to improve matching accuracy for various tattoo images—namely small tattoo images, distorted tattoo images, low-quality tattoo images. The multi-stage tattoo matching operation described throughout includes two matching stages that compare a search tattoo image against a set of reference tattoo images. In the first matching stage, the system can use scale invariant feature transform (SIFT) descriptors, or other similar types of local descriptors, to identify a list of best-matched reference tattoo images from among the set of reference tattoo images. In the second matching stage, the system uses enhanced tattoo matching techniques to verify the non-matched points and determine whether their associated areas are matched or not.

Abstract: In some implementations, an image recognition system is capable of using an iterative multi-stage image matching procedure to improve the accuracy and/or reliability of matching a search image with a small number of distinctive feature points to reference images. In the first stage, the system compares a search template for the search image to reference templates of each image within the set of reference images. The system determines a best-matched reference image from among the reference images of the set of reference images. In the second stage, the system compares the hybrid search template to one or more reference templates of reference images that is not the best-matched reference image. The comparison can be used to either compute match scores for reference images corresponding to the one or more reference templates.

Abstract: In some implementations, a method may be used for matching palm print images. A search template that identifies at least a plurality of distinctive search orientation blocks within a search orientation field may be initially generated for a search palm print image. A reference template may be obtained. A mated distinctive reference orientation block may be identified for each of the distinctive search orientation blocks. One or more regions of the search orientation field that include the distinctive search orientation blocks may be compared against one or more corresponding regions of the reference orientation field. An orientation similarity score between the search palm print image and the reference palm print image may be computed based on the comparison. A match may finally be determined if the computed orientation score satisfies a predetermined threshold value.

Abstract: In some implementations, a method includes: receiving, from the camera, a sample image that includes a fingerprint and a mensuration reference device, where the sample image is associated with a resolution; identifying (i) a plurality of edge candidate groups within the sample image, and (ii) a set of regularity characteristics associated with each of the plurality of edge candidate groups; determining that the associated set of regularity characteristics indicates the mensuration reference device; identifying a ruler candidate group, from each of the plurality of edge candidate groups, based at least on determining that the associated set of regularity characteristics indicates the mensuration reference device; computing a scale associated with the sample image based at least on extracting a set of ruler marks from the identified ruler candidate group; and generating, based at least on the scale associated with the sample image, a scaled image.

Abstract: Some implementations of the systems and techniques described include a tattoo recognition system that is capable of improving the accuracy and efficiency associated with matching edge curves extracted from tattoo images, which are typically performed during a tattoo matching operation. The system can perform a matching operation in two stages—a feature extraction stage and a matching stage. In the first stage, the system extracts one or more edge curves from the tattoo image. In the second stage, the system performs matching using a two-step comparison that compares features of the extracted edge curves.

Abstract: A method includes providing a substrate including a first fin element and a second fin element extending from the substrate, and forming a first layer including a first material over the first and second fin elements, wherein the first layer includes a gap disposed between the first and second fin elements. An anneal process is performed to remove the gap in the first layer, wherein performing the anneal process includes adjusting an energy applied to the first layer during the anneal process. The gap is filled by a portion of the first material around the gap reaching a sub-melt temperature that is different from a melting point of the first material.

Abstract: A list of possible mated minutiae in a reference fingerprint and a search fingerprint is identified. The list of possible mated minutiae is divided into different groups of mated minutiae using pose grouping based on rigid transformation parameters. For each group, the possible mated minutiae are filtered to get a set of consistent mated minutiae pairs having similar rigid transformation. The topological consistency between groups is determined. If any two groups are topologically consistent to each other, they are merged to form a (virtual) larger group. A non-linear transformation parameters are estimated from the the mated minutiae in the merged group. The overall similarity of mated and non-mated minutiae in the overlapping area is determined after non-linear alignment of the two fingerprints, and the maximum similarity is output as the final similarity score between two fingerprints.

Abstract: A semiconductor device includes a transistor having a source/drain region. A conductive contact is disposed over the source/drain region. A silicide element is disposed below the conductive contact. The silicide element has a non-angular cross-sectional profile. In some embodiments, the silicide element may have an approximately curved cross-sectional profile, for example an ellipse-like profile. The silicide element is formed at least in part by forming an amorphous region in the source/drain region via an implantation process. The implantation process may be a cold implantation process.

Abstract: A method includes providing a substrate including a first fin element and a second fin element extending from the substrate. A first layer including an amorphous material is formed over the first and second fin elements, where the first layer includes a gap disposed between the first and second fin elements. An anneal process is performed to remove the gap in the first layer. The amorphous material of the first layer remains amorphous during the performing of the anneal process.

Abstract: A fingerprint matching system for fingerprint matching using virtual minutiae includes a fingerprint scanning device, including (i) an interface to a fingerprint scanner, and (ii) a sensor associated with the fingerprint scanner, configured to identify a match between a search fingerprint representing a fingerprint of a subject and a reference fingerprint from among a plurality of reference fingerprints representing fingerprints of a plurality of historical subjects; a database containing the plurality of reference fingerprints representing fingerprints of the plurality of historical subjects; and a computing device in communication with said database and said fingerprint scanning device.

Abstract: Systems and methods may be used by an automatic fingerprint identification system to estimate ridge flow maps in latent fingerprints. A latent fingerprint image and a plurality of reference ridge flow maps may initially be obtained. A latent ridge flow map for the obtained latent fingerprint image may be computed. One or more characteristics associated with the latent ridge flow map may be compared to one or more characteristics associated with each of the plurality of reference ridge flow maps. A similarity score between the latent ridge flow map and a particular reference ridge flow map may be computed for each of the reference ridge flow maps. The top closely matched ridge flow maps are used to improve the latent ridge flow map to enhance the latent fingerprint image to extract better set of minutia points to improve latent to ten-print matching accuracy.

Abstract: In some implementations, a computer-implemented method includes: obtaining a captured image including, (i) a latent fingerprint to be captured, and (ii) a template, surrounding the latent fingerprint, that contains plurality of symbols; extracting, using an image processing technique, one or more characteristics for each of the plurality of symbols; calculating a resolution for the captured image based at least on the extracted one or more characteristics for each of the plurality of symbols; generating a reconstructed desired image, based at least on (i) the calculated resolution of the captured image, and (ii) the one or more extracted characteristics for each of the plurality of symbols; and providing the reconstructed desired image to a fingerprint identification system to perform a particular fingerprint operation.

Abstract: In one aspect, methods that use a novel representation, referred to as an octant feature vector (OFV), are used for matching distorted fingerprints. For instance, a feature-based matcher for distorted fingerprint matching may use a two-step local and global matching scheme to compare a set of feature vectors that are derived from minutiae of a reference fingerprint and a search fingerprint. The relative geometric relationships between the reference minutia and nearest minutiae may be derived and encoded into a feature vector based on orientation difference. The OFV is invariant to the rigid transformations and is insensitive to nonlinear distortions since the relative geometric relationships are independent from the rigid transformation.