Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users... more
Sign language detection and recognition (SLDR) using computer vision is a very challenging task. In respect to Bangladesh, sign language users are around 2.4 million [16]. In this paper, we try to focus for communicating with those users by computer vision. In this respect, an efficient method is proposed consists of some significant steps and they are, skin detection, preprocessing, different machine learning techniques like PCA and LDA, neural network for training and testing purpose of the system. Various hand sign images are used to test the proposed method and results are presented to provide its effectiveness.
During past few years, human hand gesture for interaction with computing devices has continues to be thriving area of research. Hand gesture Recognition system received great attention in recent years because it provides human computer... more
During past few years, human hand gesture for interaction with computing devices has continues to be thriving area of research. Hand gesture Recognition system received great attention in recent years because it provides human computer interaction and sign language. Hand gesture recognition is containing three stages: Pre-Processing, Features Extraction, classification. Most current approaches is based on the static hand gesture recognition Hand gesture recognition is often too sensitive to poor resolution ,environment of background, occultation among other prevalent problems and recognition dynamic hand gesture. So, proposed work investigates dynamic hand gesture recognition using Conditional Random Field. Result shows dynamic hand gesture recognition under complex background and achieve better recognition rate.
The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods,... more
The large numbers of images has posed increasing challenges to computer systems to store and manage data effectively and efficiently. This paper implements a CBIR system using different feature of images through four different methods, two were based on analysis of color feature and other two were based on analysis of combined color and texture feature using wavelet coefficients of an image. To extract color feature from an image, one of the standard ways i.e. color histogram was used in YCbCr color space and HSV color space. Daubechies’ wavelet transformation and Symtel’s wavelet transform were performed to extract the texture feature of an image. In this paper a color image retrieval system is illustrated, in which the novelty lies in the use of a fuzzy partition of the HSV color space and wavelet transformation of the fuzzified new image. To increase efficiency of the system finally an image retrieval method was proposed using curvelet transform of an image, which provides an opportunity to extract more accurate texture feature for image retrieval. After obtaining all experimental results, a comparative study was done. From the result it was inferred that curvelet based method gave a better performance as compared to other methods.
Copyright protection has currently become a difficult domain in reality situation. an honest quality watermarking scheme might to have high sensory activity transparency, and may even be robust enough against potential attacks. This paper... more
Copyright protection has currently become a difficult domain in reality situation. an honest quality watermarking scheme might to have high sensory activity transparency, and may even be robust enough against potential attacks. This paper tends to propose the special domain based mostly watermarking scheme for color pictures. This scheme uses the Sobel and canny edge detection strategies to work out edge data of the luminance and chrominance elements of the colour image. The edge detection strategies are used to verify the embedding capability of every color element. The massive capacities of watermark bits are embedded into an element of enormous edge information. The strength of the projected scheme is analyzed considering differing kinds of image process attacks, like Blurring and adding noise.
Facial expression recognition is an interesting and challenging problem, and found in many applications like human-computer interaction (HCI), robotics, video surveillance, border security, clinical research, person verification, crime... more
Facial expression recognition is an interesting and challenging problem, and found in many applications like human-computer interaction (HCI), robotics, video surveillance, border security, clinical research, person verification, crime prevention etc.. Facial expression is the movement of the muscles beneath the skin of the face. Through facial expressions human can convey their emotions without any verbal means. In this paper we have created raw database of color images. Training and testing set of images are created. Color information in an image is used to detect the face from the image. Important features from the detected face are extracted to form feature vectors using Gabor and Log Gabor filters. Principal Component Analysis (PCA) is used to reduce the dimension of the extracted features. Then these reduced features are classified using Euclidean distance. The main aim is to work upon three emotions-happy, neutral, surprise. Experiment carried out on self-generated database s...
Facial expression recognition (anger, sad, happy, disgust, surprise, fear expressions) is application of pattern recognition and classification task. Through facial expression human beings can show their emotions. Its applications are in... more
Facial expression recognition (anger, sad, happy, disgust, surprise, fear expressions) is application of pattern recognition and classification task. Through facial expression human beings can show their emotions. Its applications are in human-computer interaction (HCI), robotics, border security systems, forensics, video conferencing, user profiling for customer satisfaction, physiological research etc. This paper presented a Facial Expression Recognition system based using Log Gabor Filter and PCA. Euclidean distance is used as a classifier. The proposed system is designed and tested with FEI database. Two emotions to be recognized are happy and neutral.
Blood is the main component of human body. Blood is composed of Red Blood Cells, White Blood Cells, Platelets and other artifacts. Blood is considered as the main source of identifying various diseases like Malaria, Anemia, and Leukemia... more
Blood is the main component of human body. Blood is composed of Red Blood Cells, White Blood Cells, Platelets and other artifacts. Blood is considered as the main source of identifying various diseases like Malaria, Anemia, and Leukemia etc. In these diseases the main region of interests are the blood cells. The main focus in these diseases is to carefully check the blood cells because these cells in one way or another are either attacked by the parasites or some disorder in their shapes, sizes and colors. These features of blood cells have fundamental importance in the study, because different disorders result in different diseases. Due to the challenges in the light microscopy the digital images produced are noisy and need proper processing, that the features like size, shape, color and internal features like nucleus its size and color (WBC) of the various blood cells are clearly studied. This work mainly focuses on the enhancement of contrast in the YCbCr color for algorithms lik...
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color... more
Steganography is the art and science of covert communication. The secret information can be concealed in content such as image, audio, or video. This paper provides a novel image steganography technique to hide both image and key in color cover image using Discrete Wavelet Transform (DWT) and Integer Wavelet Transform (IWT). There is no visual difference between the stego image and the cover image. The extracted image is also similar to the secret image. This is proved by the high PSNR (Peak Signal to Noise Ratio), value for both stego and extracted secret image. The results are compared with the results of similar techniques and it is found that the proposed technique is simple and gives better PSNR values than others.
