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Breast cancer is one of the major causes of death among women around the world. To diagnose this disease using mammography technique, segmentation is an important step to detect the suspicious region(s) of mammograms. Segmentation concerns to the process of division of mammograms into different sections. Objective of segmentation is to simply modify the presentation of an image so that it becomes...
Underwater image segmentation becomes a difficult and challenging task due to various perturbations present in the water. In this paper we propose a novel method for underwater image segmentation based on M-band wavelet transform and human psychovisual phenomenon(HVS). The M-band wavelet transform captures the texture of the underwater image by decomposing the image into sub bands with different scales...
In this paper, we approach the problem of segmentation-free query-by-string word spotting for handwritten documents. In other words, we use methods inspired from computer vision and machine learning to search for words in large collections of digitized manuscripts. In particular, we are interested in historical handwritten texts, which are often far more challenging than modern printed documents....
Nowadays, an efficient image segmentation process as a preprocessing step provides important cues for numerous applications in human pose estimation, computer vision, objects recognition, tracking and image analysis. Many of the existing segmentation algorithms have high computational cost because of the segmentation foreground object from the large and complex-background images. But, some objects...
Although many adaptive background subtraction methods have been proposed for image-based foreground detection, dynamic background in the scene, such as an electronic billboard, still causes a serious problem of false alarm. Exclusion of such area from region of interest may prevent the problem, however an issue of security hole on that area becomes another concern. A method of change detection on...
Nowadays, handwriting recognition systems has plays an important role in our life. It allows a person scribbles words on a paper and changes them to text. There are many activities such as depositing cheque that the handwriting recognition is needed. However, there are enumerable pattern that each character could be written by one person. Our paper is focused on procedure to classify which character...
Image edge information is very important in application areas such as machine learning, image processing, stereo vision, object tracking and pattern recognition. Intensity discontinuities or sudden intensity changes in a region are indicative of the edge region in that region. Although there are many approaches to detecting edge, generally intensity discontinuities or sudden intensity changes in a...
As vast amount of digital image data is stored by the advanced libraries, there is a requirement for an efficient query word searching methodologies which can make them accessible according to user's requirement. For their accurate retrieval, it is essential to understand their contents. Present technologies for optical character recognition (OCR) and image document analysis do not handle such documents...
Image processing is a technique that can be applied on medical images for detecting abnormalities such as tumors. Due to risk of malignancy, detecting and diagnosing of cold nodules in thyroid gland are important. We applied Image Enhancement (circular averaging filter, morphological opening by diamond structure element, division of results, transforming colorful image in to gray image), Image segmentation...
In this paper we propose a new algorithm to rearrange handwriting for Thai online handwriting beautification. First, we segment the line into the right group (Line of tone level, Line of upper level, Line of body level and Line of lower level). Then we calculate the center point of each character by x average and y average value. After that we find the moving path that includes two perpendicular marks...
In this paper, we propose an automatic thresholding method based on 2D Tsallis-Havrda-Charvat entropy and histogram of local binary patterns (LBP). Tsallis-Havrda-Charvat entropy is extracted from 2D histogram, which is calculated by using the LBP decimal value of a pixel and the average decimal value of its local neighborhood. Few parameters influenced the thresholding results. Therefore, an automatic...
In process of computer-aided detection of anomaly regions in mammography images, the pectoral muscle region may involve false positives. In this study, instead of extracting pectoral muscle region after detecting its boundary, elimination of false positives in this region is aimed by a ruled-based classification technique. A topographic representation that is called as iso-level contours map is used...
This paper explores how technological advances can help in better diagnosis of cancer affected region of the brain. There has been exponential increase in brain tumor cases in recent pasts and there has been a gap in existing technology for root cause analysis. New reports indicate that various brain tumors can be treated through surgery and in exceptional cases with radiation. Image segmentation...
Clustering algorithms have materialized as an unconventional tool to precisely examine the immense volume of data produced by present applications. In specific, their main objective is to classify data into clusters such that objects are grouped in the same cluster when they are similar rendering to particular metrics and dissimilar to objects of other groups. From the machine learning perspective...
Entire brain consists of several tissues specifically gray matter (GM), white matter (WM) and cerebrospinal fluid CSF. From brain image it is troublesome to delineate these tissue regions exclusively since these regions are not well defined by sharp boundaries. In present paper a combination of approaches namely bias-field corrected fuzzy C-means and level set segmentation are presented for brain...
The research on video has been developing along with the research of the digital image processing and technological advances. The development of the internet has led to the increased production of negative images and video content. There are many challenges faced in creating filtering systems for negative content, especially on video. Most researches on the negative content filtering have been based...
In this paper, we present an interactive multimedia artwork, which awakens motionless images to interactive animations. This animation simulates the colour-flow movement from painting images. Particle movement and interaction present the rhythm of the brushstrokes. This artwork conveys lively image feelings. Human colour perception is the main idea of this work. We use image-processing techniques...
Object segmentation is a key step in image analysis and the most difficult low-level image analysis tasks, specifically in the semantic objects approach. This approach is widely implemented in various domains including fruit images. Object segmentation using OHTA colour space is one of successful methods to separate fruit object and background. However, the method is prone to remove shadows or other...
Differential box-counting (DBC) is one of the commonly used methods to estimate fractal dimension (FD) for gray scale images. It has been successfully applied in many applications such as image segmentation, pattern recognition, texture analysis and medical signal analysis. However, the accuracy improvement of FD estimation is still a grand challenge. This paper proposes a modified differential box-counting...
In this paper, we make a report our research about intensity average value of image segmentation for infrared image of air pollution. Infrared image of environmental condition (captured sequentially every two hours, from 06:00–16:00) processed using wavelet transform. After that processed, used image segmentation to get intensity average value distribution from 0 till 255 to obtain trending graphic...
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