Automatic segmentation

We present an efficient Hough transform for automatic detection of cylinders in point clouds. As cylinders are one of the most frequently used primitives for industrial design, automatic and robust methods for their detection and fitting are essential for reverse engineering from point clouds. The current methods employ automatic segmentation followed by geometric fitting, which requires a lot of manual interaction during modelling. Although Hough transform can be used for automatic detection of cylinders, the required 5D Hough space has a prohibitively high time and space complexity for most practical applications. We address this problem in this paper and present a sequential Hough transform for automatic detection of cylinders in point clouds. Our algorithm consists of two sequential steps of low dimensional Hough trans- forms. The first step, called Orientation Estimation, uses the Gaussian sphere of the input data and performs a 2D Hough Transform for finding strong hypotheses ...

Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confusion with pathological tissue. However, segmentation is a challenging problem due to low contrast and versatile appearance of the esophagus. In this paper, a two step method is proposed which first finds the approximate shape using a "detect and connect" approach. A classifier is trained to find short segments of the esophagus which are approximated by an elliptical model. Recently developed techniques in discriminative learning and pruning of the search space enable a rapid detection of possible esophagus segments. Prior shape knowledge of the complete esophagus is modeled using a Markov chain framework, which allows efficient inferrence of the approximate shape from the detected candidate segments. In a refinement step, the surface of the detected shape is non-rigidly deformed to better fit the...

Hepatic-vessel trees are the key structures in the liver. Knowledge of the hepatic-vessel tree is required because it provides information for liver lesion detection in the computer-aided diagnosis (CAD) system. However, hepatic vessels cannot easily be distinguished from other liver tissues in plain CT images. Automated segmentation of hepatic vessels in plain (non-contrast) CT images is a challenging issue. In this paper, an approach to automatic segmentation of hepatic vessels is proposed. The approach consists of two processing steps: enhancement of hepatic vessels and hepatic-vessel extractions. Enhancement of the vessels was performed with two techniques: (1) histogram transformation based on a Gaussian function; (2) multi-scale line filtering based on eigenvalues of a Hessian matrix. After the enhancement of the vessels, candidates of hepatic vessels were extracted by a thresholding method. Small connected regions in the final results were considered as false positives and we...

A reading-based CAPTCHA, called ‘ScatterType, ’ designed to resist character–segmentation attacks, is described. Its challenges are pseudorandomly synthesized images of text strings rendered in machine-print typefaces: within each image, characters are fragmented using horizontal and vertical cuts, and the fragments are scattered by vertical and horizontal displacements. This scattering is designed to defeat all methods known to us for automatic segmentation into characters. As in the BaffleText CAPTCHA, English-like but unspellable text-strings are used to defend against known-dictionary attacks. In contrast to the PessimalPrint and BaffleText CAPTCHAs (and others), no physics-based image degradations, occlusions, or extraneous patterns are employed. We report preliminary results from a human legibility trial with 57 volunteers that yielded 4275 CAPTCHA challenges and responses. ScatterType human legibility remains remarkably high even on extremely degraded cases. We speculate that...

Human skeletal remains are analysed by forensic anthropologists in order to draw conclusions about the probable identity of the deceased. During the analysis, the skull is used, along with other bones, to help determine the identity of the decedent. If only the base of the skull is available, forensic researchers take manual measurements from the large oval aperture in this region, the foramen magnum, in order to obtain information about the gender of the deceased. As this operation requires human intervention, the measurements are affected by the bias introduced by the human operator. The aim of this paper is to describe a full machine vision solution to perform precise morphological measurements of the foramen magnum. The system has been designed to extract measurements from 2D and 3D data and the returned results accurately match the manual measurements.

This paper presents the results and conclusions of a study on speech segmentation system for Arabic speech. Automatic phonetic segmentation is the problem of automatically locating the boundaries between the sounds corresponding to the phones that make up a fragment of speech. The developed system accepts a speech utterance and its orthographic transcription, and generates its phonemic transcription and the segmentation information of the utterance. The system was trained using a corpus of Arabic TV news. A phonetic dictionary was also developed using orthographic-to-phonemic transcription rules. The corpus is used to develop context-independent hidden Markov models for the Arabic phonemes. The system was validated against manually segmented speech utterances.

Automatic segmentation of brachial artery and blood-flow dynamics are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose a software program that is noise tolerant and fully automatic in segmentation of brachial artery from color Doppler ultrasound images. Possibilistic C-Means clustering algorithm is applied to make the automatic segmentation. We use HSV color model to enhance the contrast of bloodstream area in the input image. Our software also provides index of hemoglobin distribution with respect to the blood flow velocity for pathologists to proceed further analysis. In experiment, the proposed method successfully extracts the target area in 59 out of 60 cases (98.3%) with field expert's verification.

This paper proposes a novel constructive learning algorithm for a competitive neural network. The proposed algorithm is developed by taking ideas from the immune system and demonstrates robustness for data clustering in the initial experiments reported here for three benchmark problems. Comparisons with results from the literature are also provided. To automatically segment the resultant neurons at the output, a tool from graph theory was used with promising results. A brief sensitivity analysis of the algorithm was performed in order to investigate the influence of the main user-defined parameters on the learning speed and accuracy of the results presented. General discussions and avenues for future works are also provided.

Automatic segmentation of these audio streams according to speaker identities, environmental and channel conditions has be-come an important preprocessing step for speech recognition, speaker recognition, and audio data mining [7], [8], [?], and [?]. In this paper, ...

... Experiments discussed in Section 4.2 are referred to different combinations of these learning strategies with the type of phonetic transcription imposed in the segmentation phase: in the following, we will refer to the use of either Manual (MSM, MNM, ANM experiments) or ...

The aim of the present study is to assess the importance of prosody in the perceptual delimitation of “units” for the spoken language, by resorting to experiments involving non-speakers of the language, filtered speech, and automatic segmentation by the software ANALOR. The three experiments test in various ways the lack of access to semantic and syntactic information, as opposed to the expert’s segmentation. Results show that quantitatively stronger prosodic cues are needed for informants without access to the syntax-semantics of the sample, especially when they are non-speakers. The analysis also suggests the existence of both universal and language-specific prosodic cues. One of the fundamental questions underlying the analysis of spoken languages is their decomposition into units that can be considered basic in terms of informational processing and communication. Even once the importance of prosody has been recognized, the basis of the decomposition remains problematic, because ...

Abstract Carotid artery stenosis is generally a constriction caused by atherosclerosis or carotid artery lumen bottleneck. Carotid arteries are located closely to bones and osteoid structures. Osteoid structures and carotid arteries are frequently confused with each other when performing vessel evaluations. This study provides a novel method for carotid artery lumen segmentation on CTA images by using automatic vessel segmentation with inverse approach, in which vessel segmentation is performed after bone region is segmented and eliminated. The region growing and random walk segmentation methods are utilized in the elimination of bone region and the vessel segmentation. The seed points in the mentioned methods are not manually determined by any starting point. In automatic segmentation, seeds are selected from the experimentally determined intervals according to the local histogram. The stages of preprocessing and post-processing are utilized for better segmentation. The tracking of vessel centers based on continuity is employed for 3D reconstruction and 3D imaging of the vessels. Experiments were conducted with different data sets including various CTA images by using the mentioned methods. As a result, dice similarity rate above 92% was achieved together with 0.16 mm Msd and 99% accuracy. It was concluded based on these results that the proposed method provides successful results in different points of common, internal, external, vertebral arteries, carotid bifurcation and locales close to osteoid structures which are deemed challenging regions for carotid artery lumen segmentation.

In this paper we have proposed a method for lungs nodule detection from computed tomography (CT) scanned images by using Genetic Algorithms (GA) and morphological techniques. First of all, GA has been used for automated segmentation of lungs. Region of interests (ROIs) have been extracted by using 8 directional searches slice by slice and then features extraction have been performed. Finally SVM have been used to classify ROI that contain nodule. The proposed system is capable to perform fully automatic segmentation and nodule detection from CT Scan Lungs images. The technique was tested against the 50 datasets of different patients received from Aga Khan Medical University, Pakistan and Lung Image Database Consortium (LIDC) dataset.

Abstract Automatic segmentation of a text stream into topically coherent segments is an important component in natural language processing tasks such as information retrieval and document summarization. Machine learning techniques can play a vital role in building an ...

In this paper we propose a machine learning approach to classify melanocytic lesions as malignant or benign, using dermoscopic images. The lesion features used in the classification framework are inspired on border, texture, color and structures used in popular dermoscopy algorithms performed by clinicians by visual inspection. The main weakness of dermoscopy algorithms is the selection of a set of

We propose an algorithm for automatically obtaining a segmentation of a rigid object in a sequence of images that are calibrated for camera pose and intrinsic parameters. Until recently, the best segmentation results have been obtained by interactive methods that require manual labelling of image regions. Our method requires no user input but instead relies on the camera fixating on

Abstract-This paper details the design and implementation of ANGY, a rule-based expert systenm in the domain of medical image processing. Given a subtracted digital angiogram of the chest, ANGY identifies and isolates the coronary vessels, while ignoring any nonves-sel ...

With the advent of essentially unlimited data storage capabili-ties and with the proliferation of the use of the Internet, it becomes reasonable to imagine a world in which it would be possible to access any of the stored information at will with a few keystrokes or voice commands. ...

... L and a shift of m. In this way the CME is calculated, obtaining View the MathML source (seeTorres and Gamero ... 2 – annoying degradation, 3 – slightly annoying degradation, 4 – audible but not annoying degradation and, 5 – inaudible degradation) (Thorpe and Shelton, 1993). ...

Abstract The early diagnosis of lymphatic system tumors heavily relies on the computerized morphological analysis of blood cells in microscopic specimen images. Automating this analysis necessarily requires an accurate segmentation of the cells themselves. In this ...

Segmentation is a central task in Musical Analysis. We can say that it is the partition of a musical flow, usually following some set of criteria, into homogeneous segments. This paper introduces the Sonic Object Segmentator (SOS), a computer tool designed for this task. The theoretical model SOS is based on is Sonic Object Oriented Analysis. It considers the sonic object as the basic component of musical structure. It is defined as the result of the combination and interaction of some statistical components that describe distribution patterns of pitches in space and time. The model also asserts that a continuity break in at least one of these components strongly points out a new structurally significant unit. SOS’ structure is based on Mathema, a multiagent system where artificial agents, each one with a specific knowledge about one of these components, and the human user cooperate in order to accomplish some task. SOS attempts to find, for a given musical work (MIDI formatted), th...

... Automatic segmentation of time-of-flight diffraction ... signals can be visualised in an A-scan presentation or stacked together to give a two-dimensional image called a B ... The probes are moved laterally from the toe passing through the ankle, the web and the head (Figure 4). In the ...

Abstract: Concatenative Text-To-Speech synthesizers join pre-recorded segments of speech data in order to produce high quality output speech. The synthesizer has to find the best segment to concatenate from an inventory of speech material. In order to do that, the inventory ...