Masanori Mizoguchi

Feature extraction method for palmprint considering elimination of creases

A new method of extracting palmprint features is presented in this report. Since palmprint images have many creases which are organized like ridges, ordinary fingerprint feature extraction algorithms are unable to extract ridges. Consequently, the goal of this research is to construct a new feature extraction method which can extract ridges under these conditions. At first, the original palmprint image is divided into local images. The ridge candidates are extracted from each local image of the palmprint. Finally, only one candidate is selected as the ridge in the local image by estimating the continuity of certain properties. Experiments with palmprint images indicate that the proposed method can extract ridges better than conventional methods, especially in areas in which both ridges and creases exist.

Image filter design for fingerprint enhancement

Fingerprint filter design and a method of enhancing fingerprint image are discussed. Two distinct filters in the Fourier domain are designed, a frequency filter corresponding to ridge frequencies and a direction filter corresponding to ridge directions on the basis of fingerprint ridge properties. An energy function for selecting image features, i.e. frequencies and directions, is defined by intensities of images obtained with the above filters and a measure of smoothness of the features. Using the image features which minimize the energy function, an enhanced image is produced from the filtered images. This image enhancement method is applied to fingerprint matching. In experiments with rolled prints, it is shown that the matching error rate is reduced by about two-thirds compared with Asais method.

Traffic measurement with a roadside vision system-individual tracking of overlapped vehicles

Traffic measurement is an essential technique in moving toward the next stage of vehicular transportation, and one which needs to be more advanced in terms of both safety and efficiency. For this technique, image sensors are more advantageous than conventional sensors because of their portability and the wide variety of information they provide. Until now, however, vehicles overlapping each other within the image plane have caused problems with measurement accuracy. Therefore, a traffic measurement algorithm which features individual vehicle tracking using a rectangular model has been developed. The algorithm is used in real-time on the real-time vision system in order to utilize traffic volume to evaluate its performance.

Two-dimensional optical buses for massively parallel processing

Optical interconnections using two-dimensional waveguides are presented. Light beams whose incident angles are greater than the critical angle of a waveguide can propagate within that waveguide, which behaves as an optical bus. Such optical buses are suitable for massively parallel processing because they have a large number fan-outs and no skew. Estimated propagation distance in the waveguides is roughly 500 mm. One to several hundred interconnections may be achieved. Glass plates with concave lenses are used to demonstrate bus operations.

Fingerprint card classification with statistical feature integration

This paper describes a fingerprint classification algorithm for an automated fingerprint identification system with a large-size ten-print card database. The classification algorithm determines a fingerprints pattern category based on a ridge structure analysis and a direction-based neural network, and computes additional feature characteristics such as core-delta distance, along with confidence indexes associated with each feature. A card preselector then integrates the set of obtained features after weighting them according to the features expected error and inherent selection capability, calculates the card similarity based on feature differences, statistically evaluates the conditional probability of each pair being a correct match, and selects the most similar subset of the database as candidates for minutiae matching. The experimental results confirm that effective classification capability of 0.2% false acceptance with 2% false rejection has been achieved.

Dataflow Graph Optimization for Dataflow Architectures a Dataflow Otimizing Compiler

In general, datafiow graph for which it is difficult to optimize quality are those used for branches (conditionals) and loops. Although a number of dataflow graph transformation schemes have taken these into accounts, the quality of graphs been produced was not compared with that of hand-written optimized graphs.

Geometric transformation algorithm for character recognition using a gradient method

This paper proposes a feedback process approach to shape transformation in OCR character recognition for achieving higher recognition rates. An input image is deformed by warping function so that the stroke in the input image and the corresponding stroke in the reference image will overlap each other as much as possible. Pattern matching between both images is accomplished at several blurring levels, and a gradient method is applied to obtain the optimal warping parameters for minimizing the distance between the images in each blurring level. Third order polynomials by expanding Affine transformations are used as warping functions. Two kinds of pattern matching experiments were carried out. First, the image generated from an original image by warping function with certain parameters was matched with the original image by the proposed method. Second, machine-printed character images of different fonts were used for pattern matching. Both experimental results show that the optimal warping parameters for global minimization of the distances were successfully determined by the combination of a coarse-to-fine pattern matching and a gradient method. The proposed method is applicable to a variety of shape compensations, based on other matching criteria.