Direct-binary search method has been used for converting complex holograms into binary format. However, this algorithm is optimized to reconstruct monochromatic digital holograms and is accurate only in a narrow-depth range. In this paper, we proposed an advanced direct-binary search method to increase the depth of field of 3D scenes reconstructed in RGB by binary holograms.

In this paper, we analyze two representative tree-based RFID anti-collision algorithms: the Query Tree protocol and the Binary Search algorithm. Based on the advantages and disadvantages of the two algorithms, we propose and evaluate two optimized anti-collision algorithms: the Optimized Binary Search, which performs better than the Query Tree Protocol with the same tag-side overhead, and the Optimized Binary Search with Multiple Collision Bits Resolution algorithm, which performs the best with an acceptable increase in tag-side processing overhead.

Although IP address lookup schemes using ternary content addressable memory (TCAM) can perform high speed packet forwarding, TCAM is much more expensive than ordinary memory in implementation cost. As a low-cost solution, binary search algorithms such as a binary trie or a binary search tree have been widely studied. This paper proposes an efficient IP address lookup scheme using balanced binary search with minimal entries and optimal prefix vectors. In the previous scheme with prefix vectors, there were numerous pairs of nearly identical entries with duplicated prefix vectors. In our scheme, these overlapping entries are combined, thereby minimizing entries and eliminating the unnecessary prefix vectors. As a result, the small balanced binary search tree can be constructed and used for a software-based address lookup in small-sized routers. The performance evaluation results show that the proposed scheme offers faster lookup speeds along with reduced memory requirements.

Halftoning is an important process to convert a gray scale image into a binary image with black and white pixels. The Direct Binary Search (DBS) is one of the well-known halftoning methods that can generate high quality binary images for middle tone of original gray scale images. However, binary images generated by the DBS have clippings, that is, have no tone in highlights and shadows of original gray scale images. The first contribution of this paper is to show the reason why the DBS generates binary images with clippings, to clarify the range of tone in original images that may have clipping, and to present a clipping-free DBS-based halftoning algorithm. The key idea is to apply the ordered dither using a threshold array generated by DBS-based method, to highlights and shadows, and then use the DBS. The second contribution is to extend the DBS to generate L-level multitone images with each pixel taking one of the intensity levels , , ..., . However, clippings appear in highlights, middle tone, and shadows of generated L-level multitone images. The third contribution of this paper is to modify the multitone version of the DBS to generate a clipping-free L-level multitone images. The resulting multitone images are so good that they reproduce the tones and the details of the original gray scale images very well.

Binary search tree and framed ALOHA algorithms are commonly adopted to solve the anti-collision problem in RFID systems. In this letter, the read efficiency of these two anti-collision algorithms is compared through computer simulations. Simulation results indicate the framed ALOHA algorithm requires less total read time than the binary search tree algorithm. The initial frame length strongly affects the uplink throughput for the framed ALOHA algorithm.

The IP routing lookup problem is equivalent to finding the longest prefix of a packet's destination address in a routing table. It is a challenging problem to design a high performance IP routing lookup architecture, because of increasing traffic, higher link speed, frequent updates and increasing routing table size. At first, increasing traffic and higher link speed require that the IP routing can be executed at wire speed. Secondly, frequent routing table updates require that the insertion and deletion operations should be simple and low delay. At last, increasing routing table size hopes that less memory is used in order to reduce cost. Although many schemes to achieve fast lookup exist, less attention is paid on the latter two factors. This paper proposed a novel pipelined IP routing lookup architecture using selective binary search on hash table organized by prefix lengths. The evaluation results show that it can perform IP lookup operations at a maximum rate of one lookup per cycle. The hash operation ratio for one lookup can be reduced to about 1%, less than two hash operations are needed for one table update and only 512 kbytes SRAM is needed for a routing table with about 43000 prefixes. It proves to have higher performance than the existing schemes.

Conventional fast block-matching algorithms, such as TSS and DSWA/IS, are widely used for motion estimation in the low-bit-rate video coding. These algorithms are based on the assumption that when searching in the previous frame for the block that best matches a block in the current frame, the difference between them increases monotonically when a matching block moves away from the optimal solution. Unfortunately, this assumption of global monotonicity is often not valid, which can lead to a high possibility for the matching block to be trapped to local minima. On the other hand, monotonicity does exist in localized areas. In this paper, we proposed a new algorithm called Peano-Hilbert scanning search algorithm (PHSSA). With the Peano-Hilbert image representation, the assumption of global monotonicity is not necessary, while local monotonicity can be effectively explored with binary search. PHSSA selects multiple winners at each search stage, minimizing the possibility of the result being trapped to local minima. The algorithm allows selection of three parameters to meet different search accuracy and process speed: (1) the number of initial candidate intervals, (2) a threshold to remove the unpromising candidate intervals at each stage, and (3) a threshold to control when interval subdivision stops. With proper parameters, the multiple-candidate PHSSA converges to the optimal result faster and with better accuracy than the conventional block matching algorithms.

Persistent data structures, introduced by Sarnak and Tarjan, have been found especially useful in designing geometric algorithms. In this paper, we present a persistent form of binary-binary search tree, and then apply this data structure to solve various geometric searching problems, such as, three dimensional ray-shooting, hidden surface removal, polygonal point enclosure searching and so on. In all applications, we are able to either improve existing bounds or establish new bounds.