The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Cervix cancer is the most common gynecological malignancy and second most common cancer among female in Malaysia after breast cancer. The objective of this study is to extract the size of nucleus and cytoplasm, as well as gray level values of cervical cells from ThinPrep images so that accurate value of those parameters can easily be obtained. An alternative approach of extracting features for Pap...
This paper describes a practical and reliable solution/approach to achieve a semi-automated sewer pipeline inspection. The central goal of this work is to detect faults in the sewer lines which are a potential threat for underground drainage system. The major challenge for sewer line inspection is the classification and interpretation of the image data that are captured mainly by CCTV cameras mounted...
Image thresholding is a very important phase in the image analysis process. However, different images have different characteristics making the traditional process of thresholding by one algorithm a very challenging task. That is because any thresholding method may be perform well for some images but for sure it will not be suitable for all images. In this paper, intelligent thresholding by training...
In the recent years human brain segmentation in three-dimensional magnetic resonance imaging (MRI) has gained a lot of importance in the field of biomedical image processing since it is the main stage for the automatic brain disease diagnosis. In this paper, we propose an image segmentation scheme to segment 3D brain tumor from MRI images through the clustering process. The clustering is achieved...
Gender recognition is a hot research topic in recent years. Human-machine interfaces or video surveillance can be greatly improved if human gender can be recognized automatically. In this study, an embedded hidden Markov model is used for gender recognition. Video, which is recorded in different angles of view, is utilized to sample properties of each gender. Ten consecutive gait frames are segmented...
The liver is a common site for the occurrence of tumors. Automatic hepatic lesion segmentation is a crucial step for diagnosis and surgery planning. This paper presents a new fully automatic technique to segment the tumors in liver structure with no interaction from user. Contrast enhancement is applied to the slices of segmented liver, then adding each image to itself to have a white image with some...
With the increasing volumes of home video footage and the need for effectively managing such archives, home movie summarisation has become an important and key research topic in the recent past. Despite growing interest from the research community, automatic summarisation remains a challenging research problem due to unrestricted capture and lack of storyline present in the home video content. In...
In this work, we propose an approach of thematisation of audiovisual (AV) documents for a research according to topics evoked in each document. The first step of our approach is to define the descriptive metadata allowing a bibliographical description of the whole documents. The second step is divided into three stages: the first one is a temporal segmentation, the second one is space segmentation...
In this paper, we describe an alternative method of the recognition of human irises with the usage of Non-Negative Matrix Factorization. The proposed method has been implemented on graphic processor unit (GPU) which makes the method usable in the real world due to short computation time.
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models can describe the scene accurately, but they come with a high computational requirements, too. Low complex models promote segmentation speed, with the drawback of a less exhaustive description. In this paper we propose an...
To recognize unlimited set of handwritten Arabic words, an efficient segmentation algorithm is needed to segment these cursive words into a limited set of primal graphemes. We propose a rule-based segmentation algorithm that segments cursive words into graphemes through collecting special feature points from the word skeleton. The development of this algorithm is motivated by the need to solve problems...
This paper describes a method using image processing and genetic algorithm-neural network (GA-NN) for automated Mycobacterium tuberculosis detection in tissues. The proposed method can be used to assist pathologists in tuberculosis (TB) diagnosis from tissue sections and replace the conventional manual screening process, which is time-consuming and labour-intensive. The approach consists of image...
Image analysis is one of the common application fields in medical especially in cytology. Visual interpretation is the core for most medical diagnostic procedure. This process is tedious especially in the existence of overlapping cells therefore it is crucial to split the overlapping cells into single ones. This study proposes an overlapping cells separation method for separating the overlapping cells...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.