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image algebra and morphological image processing III

作者： Karavias, George Stamon, Georges Scrizzi, Almanto Univ. Paris V - Univ. Rene Descartes Paris France

ISBN: (纸本)0819409421

Our problem is to find an efficient pattern-matching method in two dimensions in order to solve a puzzle automatically. The contours of the objects must first be coded in order to be analyzed. A contour descriptor code that is quite invariant to rotation, translation, and scaling of the original object is proposed. It is an extension of the Freeman and Shape Descriptor codes. The code is based on approximating the contour by linear segments and arcs. A robust segmentation method to cut up the contour in pieces well adapted to the approximation is needed. Such a method is proposed here, namely one that segments a puzzle piece in four sides using a Hough-transform based algorithm. The roughly linear segments forming each side are detected by the transform in order to detect the frontiers of each side. Each contour piece is then encoded using the before mentioned code. The resulting database of all the piece's side codes will be used in combination with morphological features, extracted from the contour codes using morphological operators, to detect pieces sharing a common side and assemble them automatically.

关键词： image processing

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A joint asymmetric watermarking and image encryption scheme

A joint asymmetric watermarking and image encryption scheme

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conference on Security, Forensics, Steganography, and Watermarking of Multimedia Contents X

作者： Boato, G. Conotter, v. De Natale, F. G. B. Fontanari, C. Univ Trent Dept Informat Engn & Comp Sci Via Sommarive 14 I-38050 Trento Italy Politecn Torino Sch Informat Technol Dept Math I-10129 Turin Italy

ISBN: (纸本)9780819469915

Here we introduce a novel watermarking paradigm designed to be both asymmetric, i.e., involving a private key for embedding and a public key for detection, and commutative with a suitable encryption scheme, allowing both to cipher watermarked data and to mark encrypted data without interphering with the detection process. In order to demonstrate the effectiveness of the above principles, we present an explicit example where the watermarking part, based on elementary linear algebra, and the encryption part, exploiting a secret random permutation, are integrated in a commutative scheme.

关键词： Digital watermarking image encryption Symmetric-key encryption Linear algebra Sensors Cameras Computer security Cryptography image processing Multimedia

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A Comparative Study on Human Spermatozoa images Classification with Artificial Neural Network Based on FOS, GLCM and morphological Features

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1st International conference on Digital image processing and Pattern Recognition (DPPR 2011)

作者： Abbiramy, v. S. Tamilarasi, A. Velammal Engn Coll Madras Tamil Nadu India Kongu Engn Coll Perundurai India

ISBN: (纸本)9783642240546;9783642240553

This paper aims to evaluate the accuracy of artificial neural network based classifiers using human spermatozoa images. Three different neural network based classifiers are used: Feed Forward Neural Network, Radial Basis Neural Network and Elman Back Propagation Neural Network. These three different classifiers were investigated to determine their ability to classify various categories of human spermatozoa images. The investigation was performed on the basis of the different feature vectors. The feature vector includes first order statistics (FOS), textural and morphological features. The extracted features are then used to train and test the artificial neural network. Experimental results are presented on a dataset of 91 images consisting of 71 abnormal images and 20 normal images. The radial basis network produced the highest classification accuracy of 60%, 75% and 70% when trained with FOS, Combined and morphological features. When feed forward neural network is trained with GLCM features, a classification accuracy of 75% is achieved.

关键词： Segmentation Gray level Co-occurrence matrix First Order Statistics Artificial Neural Network image processing Classification Spermatozoa

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Towards automatic redeye effect removal

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PATTERN RECOGNITION LETTERS 2003年第11期24卷 1767-1785页

作者： Smolka, B Czubin, K Hardeberg, JY Plataniotis, KN Szczepanski, M Wojciechowski, K Silesian Tech Univ Dept Automat Control Elect & Comp Sci PL-44101 Gliwice Poland Univ Toronto Edward S Rogers Sr Dept ECE Toronto ON M5S 3G4 Canada Gjovik Univ Coll N-2802 Gjovik Norway

The redeye effect is typically formed in amateur photographs taken with a built-in camera flash. Analysis of the available techniques and products indicates that their efficiency in correcting this artifact is limited and their performance is inconsistent. In this work we propose a user friendly solution, which could be used to restore amateur photographs. In the proposed method the redeye effect is detected using a skin detection module and eye colors are restored using morphological image processing. The new method is computationally efficient, robust to parameter settings and versatile, as it can work in conjunction with a number of skin detection methods. (C) 2002 Elsevier Science B.v. All rights reserved.

关键词： redeye removal skin detection restoration color image enhancement

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Sonar image processing Based on C-v Algorithm 1st

Sonar Image Processing Based on C-V Algorithm

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World conference on Intelligent and 3-D Technologies (WCI3DT)

作者： Li, Menglei Jiang, Hejun Hu, Yiwen Pan, Yongfei CSSC Ocean Explorat Technol Inst Co Ltd Wuxi Jiangsu Peoples R China Sci & Technol Near Surface Detect Lab Wuxi Jiangsu Peoples R China

ISBN: (纸本)9789811971860;9789811971846;9789811971839

Target detection in sonar images is a key step in the process of underwater target recognition. Due to the influence of noise and environment, the contours of targets in sonar images often have large irregularities, the image resolution is low, and the details are relatively small, making it difficult to be accurate. An underwater target is detected. The C-v algorithm based on curve evolution theory and level set method can only use an initial closed curve to detect multiple areas with similar gray values in the sonar image and can also detect target areas with internal holes, without the need for detection. Experiments have proved that through the use of threshold filtering, morphological filtering, and C-v algorithm, the target contour can be successfully extracted from the original sonar image, which is beneficial to the subsequent target recognition based on a large amount of experimental data.

关键词： Target detection Level set method C-v algorithm Sonar image processing

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Real-time image processing for the autonomous driving of a snowcat in Antarctica

Real-time image processing for the autonomous driving of a s...

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conference on Real-Time Imaging v

作者： Broggi, A vallone, U Univ Pavia Dipartimento Informat & Sistemist I-27100 Pavia Italy

ISBN: (纸本)0819439819

This paper presents the real-time vision system developed by Pavia University within the ENEA R.A.S. (Surface Antarctic Robot) project for the automatic driving of an intelligent snowcat able to follow the traces produced by other snowcats. A camera is used to acquire images of the scene in real-time;the image sequence is analyzed by a computer vision system which identifies the traces and produces a high level description of the scene. A further optional representation, in which black markers are superimposed onto the original acquired image, is transmitted to a human supervisor., located off-board. The low level part of image processing searches for patches of snow produced by the motion of preceding snowcats. They are characterized by a high variance and are generally darker than the rest of the scene. The algorithm uses a modified variance and morphological operators for low level analysis. The result of the first part of the processing is composed of a set of disjoint clusters representing possible traces that are then labelled and selected by the following high level processing. Even if the images used in this first phase come from a non-stabilized camera, the percentage of correct detection is about 95%.

关键词： autonomous vehicle computer vision traces detection extreme conditions

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morphological processor for real-time image applications

Morphological processor for real-time image applications

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conference on Electronics andStructures for MEMS

作者： González, F Tubío, O Tobajas, F De Armas, v Esper-Chaín, R Sarmiento, R Univ Las Palmas de Gran Canaria Res Inst Appl Microelect E-35017 Las Palmas Gran Canaria Spain

Mathematical morphology (MM) appears as a theory that can solve some drawbacks of the classical lineal image processing. Linear filters generate a spatial distortion from initial image, what gives as result that specific algorithms are usually needed for each process with a complexity that cannot be implemented in vLSI systems for real time image processing. MM overcome the inherent drawbacks of the linear processing based on the comparison of an initial image with some well-known geometric figures. In this paper we present the implementation of a specific processor that computes MM basic operations. Using a clock frequency of 250 MHz this processor is able to handle real time 512 X 512 pixels video images. MM allows non-linear processing of images and it is based on dilation and erosion operations using a geometric figure called structural element (SE). More complex image processing can be performed using these two basic operations. In this implementation the SE of 3 X 3 pixels was chosen. 0.6 mum HGaAs standard cells technology, from vitesse Semiconductor Corporation, has been used achieving a logic level gate description with the possibility of migration to another technologies. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： mathematical morphology image processing real time high-speed adders GaAs

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Contribution of image analysis to the definition of explosibility of fine particles resulting from waste recycling process - art. no. 66962B

Contribution of image analysis to the definition of explosib...

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conference on Applications of Digital image processing XXX

作者： Gente, v. La Marca, F. Sapienza Univ Roma Dipartimento Ingn Chim Mat Ambiente I-00184 Rome Italy

ISBN: (纸本)9780819468444

In waste recycling processes, the development of comminution technologies is one of the main actions to improve the quality of recycled products. This involves a rise in fine particles production, which could have some effects on explosibility properties of materials. This paper reports the results of experiments done to examine the explosibility of the fine particles resulting from waste recycling process. Tests have been conducted for the products derived from milling processes operated in different operative conditions. In particular, the comminution tests have been executed varying the milling temperature by refrigerant agents. The materials utilized in explosibility tests were different typologies of plastics coming from waste products (PET, ABS and PP), characterized by size lower than 1 mm. The results of explosibility tests, carried out by mean of a Hartmann Apparatus, have been compared with the data derived from image analysis procedure aimed to measure the morphological characteristics of particles. For each typology of material, the propensity to explode appears to be correlated not only to particle size, but also to morphological properties, linked to the operative condition of the milling process.

关键词： cryogenic comminution explosibility image analysis waste recycling

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An Efficient Iris Segmentation Approach

An Efficient Iris Segmentation Approach

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International conference on Graphic and image processing (ICGIP)

作者： Gomai, A. El-Zaart, A. Mathkour, H. King Saud Univ Coll Comp & Informat Sci Dept Comp Sci Riyadh Saudi Arabia

ISBN: (纸本)9780819489326

Iris recognition system became a reliable system for authentication and verification tasks. It consists of five stages: image acquisition, iris segmentation, iris normalization, feature encoding, and feature matching. Iris segmentation stage is one of the most important stages. It plays an essential role to locate the iris efficiently and accurately. In this paper, we present a new approach for iris segmentation using image processing technique. This approach is composed of four main parts. (1) Eliminating reflections of light on the eye image based on inverting the color of the grayscale image, filling holes in the intensity image, and inverting the color of the intensity image to get the original grayscale image without any reflections. (2) Pupil boundary detection based on dividing an eye image to nine sub-images and finding the minimum value of the mean intensity for each sub-image to get a suitable threshold value of pupil. (3) Enhancing the contrast of outer iris boundary using exponential operator to have sharp variation. (4) Outer iris boundary localization based on applying a gray threshold and morphological operations on the rectangular part of an eye image including the pupil and the outer boundaries of iris to find the small radius of outer iris boundary from the center of pupil. The proposed approach has been tested on CASIA v1.0 iris image database and other collected iris image database. The experimental results show that the approach is able to detect pupil and outer iris boundary with high accuracy results approximately 100% and reduce time consuming.

关键词： iris segmentation pupil detection minimum and mean intensity of pupil iris recognition system image processing tools

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A Novel Method for Indian vehicle Registration Number Plate Detection and Recognition using image processing Techniques

A Novel Method for Indian Vehicle Registration Number Plate ...

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International conference on Computational Intelligence and Data Science (ICCIDS)

作者： varma, Ravi Kiran P. Ganta, Srikanth Krishna, Hari B. Praveen, S. v. S. R. K. MVGR Coll Engn Vizianagaram AP India CMR Engn Coll Hyderabad Telangana India Commvault Bangalore Karnataka India

Number Plate recognition, also called License Plate realization or recognition using image processing methods is a potential research area in smart cities and Internet of Things. Many of the existing automated number plate recognition systems work only in a controlled environment where images are captured from a straight angle with good illumination, clarity and standard fonts. Another drawback of existing works is that, they are based on UK number plates and may not suite for Indian number plates. This paper presents a novel image processing system for Indian number plate detection and recognition that can deal with, noisy, low illuminated, cross angled, non-standard font number plates. This work employs several image processing techniques such as, morphological transformation, Gaussian smoothing, and Gaussian thresholding in the pre-processing stage. Next, for number plate segmentation, contours are applied by border following and contours are filtered based on character dimensions and spatial localization. Finally, after the region of interest filtering and de-skewing, K-nearest neighbor algorithm is used for character recognition. The proposed methods demonstrated promising results. (C) 2020 The Authors. Published by Elsevier B. v.

关键词： image processing Number Plate Detection License plate detection vehicle number plate recognition character recognition

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