Sharif Digital Repository

Processing time and segmentation quality are two main factors in evaluation of image segmentation methods. Oversegmentation is one of the most challenging problems that significantly degrade the segmentation quality. This paper presents a framework for decreasing the oversegmentation rate and improving the processing time. Significant variations in both color and texture spaces are the main reasons that lead to oversegmentation. We exploit Affine Invariant Region Detectors to mark regions with high variations in both color and texture spaces. The results are then utilized to reduce the oversegmentation rate of image segmentation algorithms. The performance of the proposed framework is... 

This paper presents a new segmentation method for color images. It relies on soft and hard segmentation processes. In the soft segmentation process, a cellular learning automata analyzes the input image and closes together the pixels that are enclosed in each region to generate a soft segmented image. Adjacency and texture information are encountered in the soft segmentation stage. Soft segmented image is then fed to the hard segmentation process to generate the final segmentation result. As the proposed method is based on CLA it can adapt to its environment after some iterations. This adaptive behavior leads to a semi content-based segmentation process that performs well even in presence of... 

Threshold selection for text segmentation is an essential preprocessing step in most document processing algorithms. Although there are a number of sophisticatedly well-trained methods for text extraction, many researchers still prefer a fast and simple threshold selection algorithm for preprocessing. In this paper, a new global threshold selection method is proposed based on fuzzy expert systems (FESs). It initially enhances image contrast by using a FES. Then, the range of the threshold value is adjusted by using another FES and a pixel-counting algorithm. Finally, the threshold value is obtained as the middle value of the above range. To evaluate the performance of the proposed algorithm,... 

In this study, we have utilized 3-D micro-tomography images of real and synthetic rocks to introduce two mathematical correlations which estimate the distribution parameters of 3-D coordination number using a single 2-D cross-sectional image. By applying a watershed segmentation algorithm, it is found that the distribution of 3-D coordination number is acceptably predictable by statistical analysis of the network extracted from 2-D images. In this study, we have utilized 25 volumetric images of rocks in order to propose two mathematical formulas. These formulas aim to approximate the average and standard deviation of coordination number in 3-D pore networks. Then, the formulas are applied... 

Segmentation of a scene to the part made is a challenging work. In this paper a graphical model is used for this task. The methods based on geometrical derivatives such as curvature and normal often haven't good result in segmentation of geometrically-complex architecture and lead to over-segmentation and even failure. Proposed method for segmentation contains two steps. At first region growing based on curvature, normal and color is used for growing region. This segmented cloud is used for unary potential in graphical model. Fully connected graph for Conditional Random Field with Gaussian kernel for pair wise potentials is used for correcting this segmentation. Gaussian kernels are based on... 

We study a new class of visibility problems based on the notion of α-visibility. Given an angle α and a collection of line segments in the plane, a segment t is said to be α-visible from a point p, if there exists an empty triangle with one vertex at p and the side opposite to p on t such that the angle at p is α. In this model of visibility, we study the classical variants of point visibility, weak and complete segment visibility, and the construction of the visibility graph. We also investigate the natural query versions of these problems, when α is either fixed or specified at query time  

Linear segmentation of a meeting conversation is beneficial as a stand-alone system (to organize a meeting and make it easier to access) or as a preprocessing step for many other meeting related tasks. Such segmentation can be done according to two different criteria: topic in which a meeting is segmented according to the different items in its agenda, and function in which the segmentation is done according to the meeting's different events (like discussion, monologue). In this article we concentrate on the function segmentation task and propose new unsupervised methods to segment a meeting into functionally coherent parts. The first proposed method assigns a score to each possible boundary... 

Echocardiography as a common place device has been widely used for diagnosis. Segmentation of left ventricle just using the standard level set formulation based on the magnitude of intensity cannot restrict the contour evolution completely due to the lack of sharp edges. This paper aims to introduce a robust method for segmentation of three-dimensional echocardiography images based on two boundary maps namely distance map and probabilistic map as stopping criteria of contour evolution which are extracted using two different approaches. The distance map is extracted by applying Free Form Deformation (FFD) method on manually determined landmarks of initial spherical volume to register the... 

Musculoskeletal models represent spinal motion segments by spherical joints/beams with linear/nonlinear properties placed at various locations. We investigated the fidelity of these simplified models (i.e., spherical joints with/without rotational springs and beams considering nonlinear/linear properties) in predicting kinematics of the ligamentous spine in comparison with a detailed finite element (FE) model while considering various anterior-posterior joint placements. Using the simplified models with different joint offsets in a subject-specific musculoskeletal model, we computed local spinal forces during forward flexion and compared results with intradiscal pressure measurements. In... 

This paper proposes a noninvasive, acoustic-based method to differentiate between individuals with and without dysphagia or swallowing dysfunction. Swallowing sound signals, both normal and abnormal (i.e., at risk of some degree of dysphagia) were recorded with accelerometers over the trachea. Segmentation based on waveform dimension trajectory (a distance-based technique) was developed to segment the nonstationary swallowing sound signals. Two characteristic sections emerged, Opening and Transmission, and 24 characteristic features were extracted and subsequently reduced via discriminant analysis. A discriminant algorithm was also employed for classification, with the system trained and... 

For a set of n disjoint line segments S in R2, the visibility testing problem (VTP) is to test whether the query point p sees a query segment s∈S. For this configuration, the visibility counting problem (VCP) is to preprocess S such that the number of visible segments in S from any query point p can be computed quickly. In this paper, we solve VTP in expected logarithmic query time using quadratic preprocessing time and space. Moreover, we propose a (1+δ)-approximation algorithm for VCP using at most quadratic preprocessing time and space. The query time of this method is Oε (1/δ 2√n) where Oε (f(n))=O(f(n)nε) and ε>0 is an arbitrary constant number  

Breast cancer is regarded as one of the most frequent mortality causes among women. As early detection of breast cancer increases the survival chance, creation of a system to diagnose suspicious masses in mammograms is important. In this paper, two automated methods are presented to diagnose mass types of benign and malignant in mammograms. In the first proposed method, segmentation is done using an automated region growing whose threshold is obtained by a trained artificial neural network (ANN). In the second proposed method, segmentation is performed by a cellular neural network (CNN) whose parameters are determined by a genetic algorithm (GA). Intensity, textural, and shape features are... 

In this article we tackle the problem of multi-party conversation summarization. We investigate the role of discourse segmentation of a conversation on meeting summarization. First, an unsupervised function segmentation algorithm is proposed to segment the transcript into functionally coherent parts, such as Monologuei (which indicates a segment where speaker i is the dominant speaker, e.g., lecturing all the other participants) or Discussionx1x2,...,xn (which indicates a segment where speakers x 1 to xn involve in a discussion). Then the salience score for a sentence is computed by leveraging the score of the segment containing the sentence. Performance of our proposed segmentation and... 

Teeth segmentation in computed tomography (CT) images is a major and challenging task for various computer assisted procedures. In this paper, we introduced a hybrid method for quantification of teeth in CT volumetric dataset inspired by our previous experiences and anatomical knowledge of teeth and jaws. In this regard, we propose a novel segmentation technique using an adaptive thresholding, morphological operations, panoramic re-sampling and variational level set algorithm. The proposed method consists of several steps as follows: first, we determine the operation region in CT slices. Second, the bony tissues are separated from other tissues by utilizing an adaptive thresholding technique... 

Nowadays, OCR (Optical Character Recognition) is widely used for converting written documents to digital documents. One of the OCR phases is page segmentation. In page segmentation, text regions must be found in input image. In addition, text parts like text columns must be separated. In this paper, a new method for segmenting Persian/Arabic printed text is proposed. This method is based on Ink Spread Effect idea, a new idea that has particular features. Main features of Persian/Arabic scripts are considered in designing this method. This method is skew resistant and can segment text within frames and tables or regions with gray background. © 2006 ICASE  

Segmentation is a very important stage of Farsi/Arabie character recognition systems. A new segmentation algorithm -for multi font Farsi/Arabic texts- based on the conditional labeling of the up contour and down contour is presented. A pre-processing technique is used to adjust the local base line for each subword. This algorithm uses adaptive base line for each subword to improve the segmentation results. This segmentation algorithm, in addition to up and down contours, takes advantage of their curvatures also. The algorithm was tested on a data set of printed Farsi texts, containing 22236 characters, in 18 different fonts. 97% of characters were correctly segmented. © 2005 IEEE  

The goal of image segmentation is to find regions that represent objects or meaningful parts of objects. In this paper a new method is presented for color image segmentation which involves the ideas used for community detection in social networks. In the proposed method an initial segmentation is applied to partition input image into small homogeneous regions. Then a weighted network is constructed from the regions, and a community detection algorithm is applied to it. The detected communities represent segments of the image. A remarkable feature of the method is the ability to segments the image automatically by optimizing the modularity value in the constructed network. The performance of... 

The development of computer-aided diagnosis (CAD) for breast magnetic resonance (MR) images has encountered some big challenges. One of these challenges is related to breast lesion segmentation. Accurate segmentation of breast lesions has a vital role in other consequent applications such as feature extraction. Since malignant breast lesions typically appear with irregular borders and shapes in MR images whereas benign masses appear with more regular shapes, and smooth and lobulated borders, it seems that the accurate segmentation of breast lesion borders in MR images are important. To achieve this purpose, we have used the Gradient Vector Flow (GVF) snake segmentation method. This study...