The Euler number is an important topological property in a binary image, and it can be computed by counting certain bit-quads in the binary image. This paper proposes a further improved bit-quad-based algorithm for computing the Euler number. By scanning image rows two by two and utilizing the information obtained while processing the previous pixels, the number of pixels to be checked for processing a bit-quad can be decreased from 2 to 1.5. Experimental results demonstrated that our proposed algorithm significantly outperforms conventional Euler number computing algorithms.

Conventional Nyquist folding receiver (NYFR) uses zero crossing rising (ZCR) voltage times to control the RF sample clock, which is easily affected by noise. Moreover, the analog and digital parts are not synchronized so that the initial phase of the input signal is lost. Furthermore, it is assumed in most literature that the input signal is in a single Nyquist zone (NZ), which is inconsistent with the actual situation. In this paper, we propose an improved architecture denominated as a dual-channel NYFR with adjustable local oscillator (LOS) and an information recovery algorithm. The simulation results demonstrate the validity and viability of the proposed architecture and the corresponding algorithm.

In this letter, we propose a channel-aware scheduling algorithm to support real-time applications in wireless multimedia sensor networks. Multimedia streams are sensitive to real-time delivery but can tolerate some packet loss. Therefore, this specific application is modelled as an (m,k)-firm stream. To satisfy the real-time requirements, a scheduling scheme that provides packet partitioning and real-time delivery is proposed. Packet partitioning combines static assignment and dynamic adjustment while considering the channel state. The scheme is designed to minimize the number of mandatory packets delivered in a bad channel state to avoid dynamic failure. In addition, automatic repeat request technology is introduced to enhance the reliability of real-time delivery. Simulations and analyses show that the proposed scheme has a good ability to withstand a bad channel status.

This paper presents a new connected component labeling algorithm. The proposed algorithm scans image lines every three lines and processes pixels three by three. When processing the current three pixels, we also utilize the information obtained before to reduce the repeated work for checking pixels in the mask. Experimental results demonstrated that our method is more efficient than the fastest conventional labeling algorithm.

In this letter, a flexible and compatible with fine resolution radar frequency measurement receiver is designed. The receiver is implemented on the platform of Virtex-5 Field Programmable Grid Array (FPGA) from Xilinx. The Digital Down Conversion (DDC) without mixer based on polyphase filter has been successfully introduced in this receiver to obtain lower speed data flow and better resolution. This receiver can adapt to more modulation types and higher density of pulse flow, up to 200000 pulses per second. The measurement results indicate that the receiver is capable of detecting radar pulse signal of 0.2us to 2.5ms width with a major frequency root mean square error (RMSE) within 0.44MHz. Moreover, the wider pulse width and the higher decimation rate of DDC result in better performance. This frequency measurement receiver has been successfully used in a spaceborne radar system.

The Euler number of a binary image is an important topological property for pattern recognition, image analysis, and computer vision. A famous method for computing the Euler number of a binary image is by counting certain patterns of bit-quads in the image, which has been improved by scanning three rows once to process two bit-quads simultaneously. This paper studies the bit-quad-based Euler number computing problem. We show that for a bit-quad-based Euler number computing algorithm, with the increase of the number of bit-quads being processed simultaneously, on the one hand, the average number of pixels to be checked for processing a bit-quad will decrease in theory, and on the other hand, the length of the codes for implementing the algorithm will increase, which will make the algorithm less efficient in practice. Experimental results on various types of images demonstrated that scanning five rows once and processing four bit-quads simultaneously is the optimal tradeoff, and that the optimal bit-quad-based Euler number computing algorithm is more efficient than other Euler number computing algorithms.

This paper proposes a new algorithm for substring searching. Our algorithm is an improvement on the famous BM algorithm. When a mismatch happens while searching a substring (pattern), the BM algorithm will use two strategies to calculate shifting distances of the substring respectively and selects the larger one. In comparison, our algorithm uses each of the two strategies for their most suitable cases separately without a selection operation. Experimental results demonstrated that our algorithm is more efficient than the BM algorithm and the Quick Search algorithm, especially for binary strings and DNA strings.

This paper proposes an efficient two-scan labeling algorithm for binary hexagonal images. Unlike conventional labeling algorithms, which process pixels one by one in the first scan, our algorithm processes pixels two by two. We show that using our algorithm, we can check a smaller number of pixels. Experimental results demonstrated that our method is more efficient than the algorithm extended straightly from the corresponding labeling algorithm for rectangle binary images.

This paper proposes a graph-theory-based Euler number computing algorithm. According to the graph theory and the analysis of a mask's configuration, the Euler number of a binary image in our algorithm is calculated by counting four patterns of the mask. Unlike most conventional Euler number computing algorithms, we do not need to do any processing of the background pixels. Experimental results demonstrated that our algorithm is much more efficient than conventional Euler number computing algorithms.