This paper proposes modification of the conventional Sum of Absolute Differences (SAD) for performance improvement in depth-map estimation from stereo images captured by a camera in a stereo system. The conventional SAD is commonly search in whole stereo images to find out the difference in pixels between the left and right captured images, and then obtains the corresponding disparity map and this may lead to high elapsing time. In order to reduce the number of searching pixels, the proposed modified SAD tries to estimate the difference only from edge pixels which are referred as pixels-ofinterest and bring significant information about depth map. The number of pixels being searched is reduced to about 17% on the total pixels, hence the total elapsing time is saved up to around 89% compared to that of the conventional SAD. This results is promising for implementation of a real-time vision system. Keywords-sum of absolute difference, stereo camera, disparity map, stereo visionI.

Locating facial feature in face images is an important stage for numerous facial image applications such as face recognition, face expression recognition and face tracking and lip reading. In this paper, we present a robust method for detecting facial feature points in frontal face images. The method adopts face detection algorithm of Viola-Jones face detector. The facial regions are than extracted by applying Haar feature based Adaboost algorithm for detecting eye, nose and mouth regions. Finally, template matching and several image processing techniques are utilized to detect feature points. Experiment on the IMM database, CVL database and our laboratory database is carried out to demonstrate and verify the proposed method.

Fractal Image Compression (FIC) method provides a color image compression solution with an extremely high compression ratio, however it requires relative large amount of operations to complete codification. In this paper, we have developed an efficient approach for a fractal image compression applied to a color image, which utilizes a fractal coding on RGB to YCrCb color transformation and suitable sampling modes, then implemented on FPGA board. The experimental results performed by Fisher's method for a color image have verified the possibility to design a SoC for fast fractal coder/decoder of a color image.

In this paper, a low-power and low-noise capacitive-coupled chopper instrumentation amplifier (CCIA) is proposed for biopotential sensing applications. A chopping technique is applied to mitigate the domination of flicker noise at low frequency. A new offset cancellation loop is also used to deal with the intrinsic offset, originating from process variation, to reduce ripple noise at the output of CCIA. Moreover, the optimization of the chip area was resolved by adding a T-network capacitor in the negative feedback loop. The CCIA is designed on 0.18 µm process CMOS technology with a total chip area of 0.09 mm2. The post-simulation results show that the proposed architecture can attenuate the output ripple up to 41 dB with a closed-loop gain of 40 dB and up to 800 Hz of bandwidth. The integrated input referred noise (IRN) of the CCIA is 1.8 µVrms over a bandwidth of 200 Hz. A noise efficiency factor (NEF) of 5.4 is obtained with a total power dissipation of 1.2 µW and a supply voltage of 1 V, corresponding to a power efficiency factor of 9.7 that is comparable with that of state-of-the-art studies.

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