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Accurate spleen segmentation in abdominal MRI images is one of the most important steps for computer aided spleen pathology diagnosis. The first and essential step for the diagnosis is the automatic spleen segmentation that is still an open problem. In this paper, we have proposed a new automatic algorithm for spleen area extraction in abdominal MRI images. The algorithm is fully automatic and contains...
The efficiency of a human face recognition system depends on the capability of face recognition in presence of different changes in the appearance of face. One of the main difficulties regarding the face recognition systems is to recognize face in different views and poses. In this paper we propose a new algorithm which utilizes the combination of texture and depth information to overcome the problem...
The recognition of handwritten characters and digits is an important and challenging issue in OCR algorithms. This article presents a new method in which cluster based weighted support vector machine is used for the classification and recognition of Farsi handwritten digits that is reasonably robust against rotation and scaling. In the proposed algorithm, after applying the necessary preprocessing...
Script recognition is a necessary process before OCR algorithm in multilingual systems. In this paper, a novel method is proposed for identifying Farsi and Latin scripts in bilingual document using curvature scale space features. The proposed features are rotation and scale invariant and can be used to identify scripts with different fonts. We assumed that the bilingual scripts may have Farsi and...
In this paper, a method for classifying room impulse responses using multifractals and Kohonen's neural networks is investigated. Impulse response is basic source of information in room acoustics; therefore its analysis is the most important issue regarding sound impression in the room. The method proposed in this paper consists of three steps. The first stage of signal classification process is computation...
This paper addresses the problem of vowels recognition in patients after total laryngectomy using combined visual and acoustic features. The linear prediction coefficients were estimated from speech signal using weighted recursive least squares algorithm. Ten cross-sectional areas of vocal tract model were calculated. Face expression parameters related to the spoken vowel were extracted from video...
This paper discusses the problem of object area detection of video frames. The goal is to design a pixel accurate detector for grass, which could be used for object adaptive video enhancement. A boosting neural network is used for creating such a detector. The resulted detector uses both textural features and color features of the frames.
In this paper, an efficient heart beat classification algorithm suitable for implementation on mobile devices is presented. A simplified ECG model is used for feature extraction in the time domain. The QRS complex is modeled using straight lines, while P and T waves are modeled using parabolas. The model parameters are estimated by minimizing the root mean square (RMS) of the model error. Heart beats...
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