Search results for "Histogram"
showing 10 items of 115 documents
Bag of words representation and SVM classifier for timber knots detection on color images
2015
Knots as well as their density have a huge impact on the mechanical properties of wood boards. This paper addresses the issue of their automatic detection. An image processing pipeline which associates low level processing (contrast enhancement, thresholding, mathematical morphology) with bag-of-words approach is developed. We propose a SVM classification based on features obtained by SURF descriptors on RGB images, followed by a dictionary created using the bag-of-words approach. Our method was tested on color images from two different datasets with a total number of 640 knots. The mean recall (true positive) rate achieved was (92%) and (97%) for a single dictionary (built only on samples …
An Unsupervised Method for Suspicious Regions Detection in Mammogram Images
2015
Over the past years many researchers proposed biomedical imaging methods for computer-aided detection and classification of suspicious regions in mammograms. Mammogram interpretation is performed by radiologists by visual inspection. The large volume of mammograms to be analyzed makes such readings labour intensive and often inaccurate. For this purpose, in this paper we propose a new unsupervised method to automatically detect suspicious regions in mammogram images. The method consists mainly of two steps: preprocessing; feature extraction and selection. Preprocessing steps allow to separate background region from the breast profile region. In greater detail, gray levels mapping transform …
Studies on the Effectiveness of Multispectral Images for Face Recognition: Comparative Studies and New Approaches
2013
In this paper, we investigate face recognition in unconstrained illumination conditions. A twofold contribution is proposed: First, three state of the art algorithms, namely Multiblock Local Binary Pattern (MBLBP), Histogram of Gabor Phase Patterns (HGPP) and Local Gabor Binary Pattern Histogram Sequence (LGBPHS) are challenged against the IRIS-M3 multispectral face data base to evaluate their robustness against high illumination variation. Second, we propose to enhance the Performance of the three mentioned algorithms, which has been drastically decreased because of the non-monotonic illumination variation that distinguishes the IRIS-M3 face database. Instead of the usual braod band images…
Concept Drift Detection Using Online Histogram-Based Bayesian Classifiers
2016
In this paper, we present a novel algorithm that performs online histogram-based classification, i.e., specifically designed for the case when the data is dynamic and its distribution is non-stationary. Our method, called the Online Histogram-based Naïve Bayes Classifier (OHNBC) involves a statistical classifier based on the well-established Bayesian theory, but which makes some assumptions with respect to the independence of the attributes. Moreover, this classifier generates a prediction model using uni-dimensional histograms, whose segments or buckets are fixed in terms of their cardinalities but dynamic in terms of their widths. Additionally, our algorithm invokes the principles of info…
Shape-Based Features for Cat Ganglion Retinal Cells Classification
2002
This article presents a quantitative and objective approach to cat ganglion cell characterization and classification. The combination of several biologically relevant features such as diameter, eccentricity, fractal dimension, influence histogram, influence area, convex hull area, and convex hull diameter are derived from geometrical transforms and then processed by three different clustering methods (Ward’s hierarchical scheme, K-means and genetic algorithm), whose results are then combined by a voting strategy. These experiments indicate the superiority of some features and also suggest some possible biological implications.
Image Segmentation and Object Extraction for Automatic Diatoms Classification
2018
The diatoms are unicellular algae of great interest in paleontology, aquatic ecology, and forensic medicine, among others. Currently, there are more than 100 000 known species distributed in aquatic ecosystems. For that reason, there is a big interest in the automatic classification of diatom images, however, the preliminary process applied to isolate the diatom from the background is a complex task. In this paper, we propose a segmentation method and an object-extraction procedure to extract the diatom from the background. First, we binarize the image by searching the optimal threshold in the histogram based on its cumulative distribution function. Then we eliminate, under some spatial cri…
Mākoņu noņemšana no satelīta attēliem
2020
Jauni satelītu attēli ir praksē noderīgi, tos izmanto dažādās jomās, piemēram, kartogrāfijā. Šajā darbā tiek apskatīti Copernicus Sentinel-2 satelītu uzņemtie Zemes attēli. Tiek izpētīta satelītu programma, rīki un datu formāti. Tiek apskatīti lēmuma koku un Beijesa klasificēšanas algoritmi, kas ļauj izgūt mākoņus un citus reģionus no attēliem, izpētīti attēlu apstrādes algoritmi, kas ļauj saskaņot dažādu attēlu vizuālo izskatu pēc attēla histogrammas datiem. Darba praktiskajā daļā tiek realizēta sistēma, kas ļauj izgūt lietotājam aktuālāko satelīta attēlu noklājumu pār ģeogrāfisku intereses reģionu. Attēli tiek veidoti kombinējot jaunākos satelīta uzņemtos d…
Real metrology by using depth map information
2004
Usually in an image no real information about the scene’s depth (in terms of absolute distance) is available. In this paper, a method that extracts real depth measures is developed. This approach starts considering a region located in the center of the depth map. This region can be positioned, interactively, in any part of the depth map in order to measure the real distance of every object inside the scene. The histogram local maxima of this region are determined. Among these values the biggest, that represents the gray-level of the most considerable object, is chosen. This gray-level is used in an exponential mapping function that converts, using the input camera settings, the depth map gr…
EMG artifacts removal during electrical stimulation, a CWT based technique
2014
International audience; A technique of artifacts removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram (EMG) signal during an electrically evoked contraction of a muscle. This method can be used with standard stimulation pulse waveforms like monophasics or biphasics ones. It uses a histogram representation to find the best threshold to apply on the CWT domain. The algotithm is presented with Haar wavelet and then it is used with common wavelet famillies such as Daubechies or Symlets.
A computer‐aided instrument for pattern recognition of partial discharges
1998
In this paper a new computer‐aided digital system for partial discharge (PD) measurements is presented. The system is able to collect a great number of data, up to a pulse repetition rate of 100kHz, during the acquisition phase, thus allowing an off‐line analysis of PD data. After a description of the instrument, some experimental tests performed on epoxy specimens are here presented in terms of amplitude, phase and energy resolved histograms. Finally, emphasis is given to the very interesting use of the instrument for pattern recognition techniques in the discrimination and classification of discharges in HV components.