A~trac t -A recursive, nonparametric method is developed for performing density estimation derived from mixture models, kernel estimation and stochastic approximation. The asymptotic performance of the method, dubbed "adaptive mixtures" (Priebe and Marchette, Pattern Recognition 24, 1197-1209 (1991)) for its data-driven development of a mixture model approximation to the true density, is invest...

In finger vein recognition, the input image is generally labeled in accordance with the nearest enrolled neighbor. However, it is so rigid that it is inadequate for some cases. This paper explores a modified sparse representation method for finger vein recognition. In the method, each block in a finger vein image will be sparsely represented by dictionary textons, not simply labeled by the near...

In image search based on chromatic similarity, the e.ectiveness of retrieval can be improved by taking into account the spatial arrangement of colors. This can serve both to distinguish images with the same colors in di.erent arrangement, and to capture the similarity between images with di.erent colors but similar arrangements. We propose a model of representation and comparison which attains ...

The method of using a lateral histogram for evaluating the number of holes (e.g., defects) from images is known to be fast but rather inaccurate. Our aim is to propose a method of improving its performance by learning, but keeping the speed of the original method. This task is accomplished by considering a multiclass pattern recognition problem with linearly ordered labels and a loss function, ...

This paper shows an experimental trial on part-based online character recognition. The purpose of the trial is to evaluate the discrimination ability of parts of a handwriting character, that is, a temporal pattern showing a character. Each part is a temporal segment of the character and the character is decomposed into a set of parts. Those parts are then represented as a “bag-of-features”, wh...

This paper introduces two spatial methods in order to embed watermark data into "ngerprint images, without corrupting their features. The "rst method inserts watermark data after feature extraction, thus preventing watermarking of regions used for "ngerprint classi"cation. The method utilizes an image adaptive strength adjustment technique which results in watermarks with low visibility. The se...

Image quality assessment (IQA) is in great demand for high quality image selection in the big data era. The challenge of reduced-reference (RR) IQA is how to use limited data to effectively represent the visual content of an image in the context of IQA. Research on neuroscience indicates that the human visual system (HVS) exhibits obvious orientation selectivity (OS) mechanism for visual conten...

This paper presents a novel feature descriptor termed principal component analysis (PCA)-based Advanced Local Octa-Directional Pattern (ALODP-PCA) for content-based image retrieval. The conventional approaches compare each pixel of an with certain neighboring pixels providing discrete information. proposed in this work utilizes the local intensity all eight directions its neighborhood. octa-dir...

Human activity recognition is an important task in computer vision because it has many application areas such as, healthcare, security, entertainment, and tactical scenarios. This paper presents a methodology to automatically recognize human activity from input video stream using Histogram of Oriented Gradient Pattern History (HOGPH) features and SVM classifier. For this purpose, the proposed s...

In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems involved in finding the minimum of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of...