The main aim of this study is to decrease the amount of storage as much as possible and the decoded image seen on the monitor should be as close as possible to the original image. The main goal of this study is to design a fully hybrid system for medical image compression. For this purpose, a hybrid techniques were used to enhance the compression performance, decreasing the computational complexity level and raising the CR (Compression Ratio, the proposed system is adopted on these tools: to design a new fully hybrid image compression system to compress a medical image (Brain Tumour disease type). Furthermore, a new reliable algorithm was proposed in order to identify the ROI (Region of Interest) and NROI (Non-Region of Interest) before compression process. In addition, this algorithm has less computational complexity and efficient, also develop new algorithms to compress the ROI and NROI regions. The first region, ROI, is compressed by cascading of SPIHT and BAT algorithms. Meanwhile, the second region (NROI) is compressed by the 2D-DWT algorithm, finally to design a new coding system by mixed the RLE (Run-Length Encoding) and Huffman coding algorithms to improve the CR. The results indicate that the SPIHT-BAT algorithm has increase the compression ratio better than SPIHT. Furthermore, the result of ROI region better than the result of NROI region. While the result of coding when used (RLE- Huffman) algorithm better than the result when used (RLE) alone or Huffman algorithm. The different parameters of compression process indicate that the proposed system is better than that of Traditional systems that described in literature.
This paper presents the act of face recognition using neural network techniques and binary pattern methods. This is aimed at devising a technique for robotic control via facial expression. The Matlab environment was used in this work to provide accurate processing of image and facial expression categorization using a neural network. By using the microcontroller board of basic stamp 2 (BS2), the wireless transmitter circuit was built in this study. Also, the receiver part was designed with a decoder and BS2 microcontroller and interfaced with MATLAB by serial port communication. The major function of BS2 is to remain for convinced typescript from MATLAB and process it to confirm the command required to be wirelessly transmitted. Through serial port to BS2, the four characters were sent by MATLAB, with one quality for every emotion detected. The gestures and facial expressions provide intuitional cues for interpersonal communication. Local Binary Pattern (LBP) features were introduced for texture analysis and recently have been introduced to represent faces in facial image analysis. The most important properties of LBP features are their computational simplicity and their tolerance to illumination changes. LBP features can be derived very fast in a single scan through the raw image and are within the low-dimensional feature space for texture analysis; they are applied as a local feature extraction method in facial expression recognition. This work introduced facial expression examination algorithms for motionless images and efficient extension to the sequence of images. The results showed that the classification accuracy achieved was 41% for static expression images and 86.31% for series of images; this is significantly higher than the accuracy of other standard image processing and recognition techniques.
This paper presents the design and optimization of image compression and ciphering depend on optimized embedded zero tree of wavelet (EZW) techniques. Nowadays, the compression and ciphering of image have become particularly important in a protected image storage and communication. The challenge is put in application for both compression and encryption where the parameters of images such as quality and size are critical in secure image transmission. A new technique for secure image storage and transmission is proposed in this work. The compression is achieved by remodel the EZW scheme combine with discrete cosine transform (DCT). Encrypted the XOR ten bits by initial threshold of EZW with random bits produced from linear-feedback shift register (LFSR). The obtained result shows that the suggested techniques provide acceptable compression ratio, reduced the computational time for both compression and encryption, immunity against the statistical and the frequency attacks.
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