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Although interactive segmentation helps lower the degree of human intervention, further upgrade to increase the efficiency and intuitiveness of interactive segmentation method remains requisite. Invariably, newly acquired medical images are not segmented instantly by radiologists due to heavy work load. Therefore, improvement can be made by capitalizing on the time interval between image acquisition...
Automatic text detection and extraction systems for natural scene images and videos have gained wide attention due to its immense applications in various fields of information retrieval. Many algorithms have been proposed in literature which addresses the problem of text detection. The color uniformity of text characters is one of the strong features which is used in color based text localisation...
Radiologists are known to suffer from fatigue and drop in diagnostic accuracy due to large number of slices to read and long working hours. A computer aided diagnosis (CAD) system could help lighten the workload. Segmentation is the first step in a CAD system. This study aims to propose an accurate automatic segmentation. This study deals with High Resolution Computed Tomography (HRCT) scans of the...
This paper presents a new region-of-interest(ROI) based compression scheme for video call applications in a preprocessing manner. In our application, ROI is the human region which is detected by a human/background segmentation method, and perceptually less important details are removed by applying the edge-preserving spatio-temporal filter to the background regions. In order to obtain the accurate...
Nowadays, it is hard to distinguish the type of orchid leaf diseases just by using naked eyes. This paper presents an image segmentation technique for classify two difference types of orchid leaf disease such as black leaf spot and sun scorch. The orchid leaves images were digitally captured by using digital camera. With respect to the region of interest selected orchid leaves are analyze by using...
This paper uses the somatosensory system of Kinect to realize the hand gesture recognition involving action and digit of finger. The hand action is completed by using the NiTE library owning the framework of hand gesture recognition. Taking advantage of the information of the depth map, the digit expressed by hand is recognized by using OpenCV library. The simulated results demonstrate the work is...
This paper presents a novel image haze removal approach from single image. In the algorithm, the constant albedo and dark channel prior methods are combined to represent the transmission model of hazed image. And then, the quick shift segmentation approach is introduced to decompose the input image into some gray level consistent areas. Compared with traditional fixed image partition schemes, better...
Depth information can be obtained using stereo matching algorithms, which compute the horizontal displacement (disparity) of the corresponding points and convert to depth information using the triangular relation. However, the matching process is challenging with presence of textureless regions. This paper proposes a novel disparity refinement method for stereo matching based on Semi-global Matching...
In this paper, a co-segmentation method to extract the cortex in inter-subject brain MR (Magnetic Resonance) images is proposed. Co-segmentation is a method to segment two images simultaneously. The method employs the MRF (Markov Random Field) based graph for contstructing the objective function and the graph-cut algorithm for opimization. In the graph construction, similarity nodes are added to represent...
In this paper, we shall describe a new iterative method of unsupervised multisensor image segmentation based on the evidence theory. We show that the modeling by means of evidence theory is well suited to the processing of redundant and complementary data as the satellite images. This theory turns out to be quite efficient in unsupervised multisensor image segmentation. The application of the evidence...
Many attempts have been made to identify the region of interest in an image. In this paper, we have provided a new approach for ROI detection using the output of image annotation. Our claim is that because ROI is a subjective concept, a method should be used to diagnosis human mental models and for this purpose, we have used KNN base annotation in our method. Because many people in pictures that are...
We present in this paper a state of the latest advances in the field of offline handwritten signature verification. We describe the main approaches that have been proposed in the recent decades. Besides, we introduce the database of static signatures published in the literature as well as international competitions organized in the domain. Also, we present our contribution in the field.
This paper present a new method to resolve the problem of the estimation of eye position in the analysis of videonystagmography(VNG) sequences, that studies eye vibration using active contour model. An algorithm for horizontal and vertical nystagmus tracking based on some parameters such as position, amplitude and duration, is presented. Indeed, the algorithm uses active contour method to segment...
In this paper we present a simple and efficient technique of color image segmentation based on new approach for color level selection among a widely set of color space. We still prove the dependence between segmentation results and the used color level. Our method is based on entropy-based thresholding that is able to separate different objects based on the calculated amount of information contributed...
The corpus callosum is one of the most important structures in human brain. Most of the neurological disorders reflect directly or indirectly on the morphological features of Corpus Callosum. The mid-sagittal brain Magnetic Resonance images fully describe the anatomical structure of corpus callosum. Often considered challenging task of segmenting Corpus Callosum from Magnetic Resonance images has...
This paper presents a method of detecting and segmenting regions of interest (ROIs) of the thermal image of electrical installations. These regions are very important in diagnosing the thermal condition of electrical equipment. Due to the nature of thermal imaging, segmentation with the conventional approach will make inaccurate ROI detection, especially when qualitative approach is considered in...
Rare colored capsule (RCC) is the capsule which is mixed in the normal product but with different color. To detect this kind of capsules online, a method based on RGB color space and using HSV color difference formula is proposed in this paper. Considering HSV color space with more balanced color-difference perception, the original RGB formatted capsule image is transformed to HSV color space for...
This paper presents a fresh food recognition system that utilizes the feature fusion extracted from food images captured from optical fibers embedded inside a chopping board. We exploit both local and global features including color, SURF and shape for image representation. In addition, we propose cost-based schemes for feature matching and the Borda count method for feature fusion. An experiment...
This paper proposes an unsupervised technique for detecting planar surfaces on single depth map image. The proposed method can detect planar surfaces by adopting dynamic seed growing technique without using texture information. So aided with this mechanism to control the growing process, each seed patch can grow to its maximum extent and then the next seed patch begins to grow. This process avoids...
In this paper, a reliable pixel-based foreground-background segmentation technique for detecting object(s) of interest (OOI) from video sequence captured by a fixed camera is proposed. OOIs, used for further tracking or positioning applications, should be detected accurately from those moving (or still) objects even under variable illumination and the corresponding background model need to update...
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