Destination Address Block Research Articles

Automatic Chinese Postal Address Block Location Using Proximity Descriptors and Cooperative Profit Random Forests

Locating the destination address block is key to automated sorting of mails. Due to the characteristics of Chinese envelopes used in mainland China, we here exploit proximity cues in order to describe the investigated regions on envelopes. We propose two proximity descriptors encoding spatial distributions of the connected components obtained from the binary envelope images. To locate the destination address block, these descriptors are used together with cooperative profit random forests (CPRFs). Experimental results show that the proposed proximity descriptors are superior to two component descriptors, which only exploit the shape characteristics of the individual components, and the CPRF classifier produces higher recall values than seven state-of-the-art classifiers. These promising results are due to the fact that the proposed descriptors encode the proximity characteristics of the binary envelope images, and the CPRF classifier uses an effective tree node split approach.

AUTOMATION OF INDIAN POSTAL DOCUMENTS WRITTEN IN BANGLA AND ENGLISH

In this paper, we present a system towards Indian postal automation based on pin-code and city name recognition. Here, at first, using Run Length Smoothing Approach (RLSA), non-text blocks (postal stamp, postal seal, etc.) are detected and using positional information, Destination Address Block (DAB) is identified from postal documents. Next, lines and words of the DAB are segmented. In India, the address part of a postal document may be written by a combination of two scripts: Latin (English) and a local (State/region) script. It is very difficult to identify the script by which pin-code part is written. To overcome this problem on pin-code part, we have used a two-stage artificial neural network based general scheme to recognize pin-code numbers written in any of the two scripts. To identify the script by which a word/city name is written, we propose a water reservoir concept based feature. For recognition of city names, we propose an NSHP-HMM (Non-Symmetric Half Plane-Hidden Markov Model) based technique. At present, the accuracy of the proposed digit numeral recognition module is 93.14% while that of city name recognition scheme is 86.44%.

서장 우편물 자동처리를 위한 우편영상 인식 시스템

본 논문에서는 우편물 자동처리론 위한 우편영상 인식 시스템을 소개한다. 우편영상 인식 시스템은 서장 우편물을 집배원이 배달하는 순서에 따라 자동으로 구분할 수 있도록 우편영상을 입력으로 받아 수신인 주소를 출력하는 인식 시스템을 말한다. 이 시스템은 수신인 주소영역 추출, 문자열 분리, 문자분할, 문자인식, 그리고 주소해석 모듈로 구성되어 있다. 주소영역 추출을 위해서는 우편물 주소 기입 위치에 대한 경험적 지식을 이용하였으며, 문자열 분리와 문자분한을 위해서는 연결요소 분석과 수직런 분석을 이용하였다. 문자인식에는 신경망 기반 인식기를 이용하였으며, 주소해석을 위해서는 동적 프로그래밍 기법을 적용하였다. 각 모듈은 독립적으로 구현되었기 때문에 인식 시스템의 성능 개선을 위한 모듈별 최적화가 용이하다는 장점이 있다. 실험에는 대전 유성우체국의 우편물 구분기를 이용하여 실제 우편물에서 수집한 인쇄 우편영상과 필기 우편영상을 이용하였으며, 비교적 우수한 인식 결과를 얻었다. In this paper, we describe an address image recognition system for automatic processing of standard- size letter mail. The inputs to the system are gray-level mail piece images and the outputs are delivery point codes with which a delivery sequence of carrier can be generated. The system includes five main modules; destination address block location, text line separation, character segmentation, character recognition and finally address interpretation. The destination address block is extracted on the basis of experimental knowledge and the line separation and character segmentation is done through the analysis of connected components and vortical runs. For recognizing characters, we developed MLP-based recognizers and dynamical programming technique for interpretation. Since each module has been implemented in an independent way, the system has a benefit that the optimization of each module is relatively easy. We have done the experiment with live mail piece images directly sampled from mail sorting machine in Yuseong post office. The experimental results prove the feasibility of our system.

택배 자동 분류를 위한 주소영역 검출 알고리즘

In this paper, we proposed the algorithm for locating destination address block (DAB) from automatic system to classify packages. For locating DAB, because the size of obtained images is are very large, we select the region of interesting (ROI) to reduce time carrying into algorithm. After selecting the ROI, proposed algorithm is carried out within the ROI. We extract the outline of the handwriting part of the DAB and the rest components within the obtained ROI using thresholding. We carry out labeling to extract each connected component for extracted outline and the rest components. We extract the outline of the handwriting part of the DAB using the geometrical characteristic of the outline of the handwriting part of the DAB among many connected components. The last, we extract the locating DAB using the outline of the handwriting part of the DAB.

Locating the destination address block on images of complex mail pieces

For automatic processing of mail, the problem of locating the destination address block (DAB) on the images of mail pieces is still a bottleneck. Using a bottom‐up approach, we locate the DAB in allusion to complex mail pieces. Our algorithm starts from local binarization between the rising and falling points in the image, following by searching, filtering, feature extraction, and modified region growing of connected components. Finally, some features of the candidate blocks are extracted for assigning weights to locate the DAB. The success of our algorithm for locating the DAB on complex mail pieces is demonstrated on 100 test images with the success rate 90.7%. The results also show that our approach can process a DAB which is skewed, hand‐written, or machine‐printed. The average processing time for each piece image of size 720×960 is 2.66 seconds on a PC (PentiumII‐400).

Location and interpretation of destination addresses on handwritten Chinese envelopes

Virtually all mail sorting machines currently used in China only recognize post code and ignore the useful destination address information on the envelopes. This paper discusses how to efficiently utilize such important information on handwritten Chinese envelopes in order to improve the sorting performance. For this purpose, two particular problems are addressed, respectively. One is the location of destination address block (DAB) on the envelope, and a new bottom-up location method is described in detail. The other is the interpretation of handwritten Chinese destination address strings. We present our effort on using as many geometric constraints as possible in the string segmentation. Then a novel address interpretation algorithm with global optimization is proposed. It combines the segmentation, recognition and address context information by the best-path search. The effectiveness of the proposed algorithms is fully demonstrated by our experiments on real envelopes.

Address block location on handwritten Korean envelopes by the merging and splitting method

In this paper, we propose a knowledge-based system for locating Destination Address Block (DAB) on handwritten Korean envelopes by the merging and splitting method. In the proposed system, the preprocessing steps such as adaptive binarization, connected component extraction, and deskewing are carried out first. Then, DAB containing address part, name part and zipcode part, of the input envelope image is extracted by an iterative procedure based on the knowledge acquired from the statistical feature analysis of the various handwritten Korean envelopes. Most of the systems for locating address blocks on the envelopes extracted DAB by segmenting an envelope image into several candidate blocks followed by selecting one among the candidate blocks. Because it is very difficult to segment a handwritten Korean envelope image into several blocks, due to the specific writing habits that the addresses on the envelope are written in close proximity to each other, the proposed iterative procedure determines DAB by merging and splitting the connected components, and verifies the determined DAB without segmentation and selection. Experiments with a great number of live handwritten Korean envelopes provided from Seoul Mail Center in Korea were carried out. Experimental results reveal that the proposed system is very effective for address block location on handwritten Korean envelopes.

Postal address block location in real time

The CEDAR real-time address block location system, which determines candidates for the location of the destination address from a scanned mail piece image, is described. For each candidate destination address block (DAB), the address block location (ABL) system determines the line segmentation, global orientation, block skew, an indication of whether the address appears to be handwritten or machine printed, and a value indicating the degree of confidence that the block actually contains the destination address. With 20-MHz Sparc processors, the average time per mail piece for the combined hardware and software system components is 0.210 seconds. The system located 89.0% of the addresses as the top choice. Recent developments in the system include the use of a top-down segmentation tool, address syntax analysis using only connected component data, and improvements to the segmentation refinement routines. This has increased top choice performance to 91.4%.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

A framework for object recognition in a visually complex environment and its application to locating address blocks on mail pieces

A computational framework for recognizing an object of interest in a complex visual environment is developed. Arising from the problem of finding the destination address block on a mail piece, a general framework for coordinating a collection of specialized image analysis tools is described. The framework is based on the blackboard model of problem-solving with enhancements to account for object recognition in a visually complex environment. Those enhancements include (i) a systematic derivation of knowledge sources that describes a methodology for developing knowledge sources in an application domain, (ii) a dependency graph to specify the interdependency between knowledge sources, (iii) a control mechanism that detects the varying degrees of complexity in the input, and adjust the behavior of the system so that the effort expended in gathering evidence is in accordance with the complexity of inputs, (iv) a formalism for estimating the utility of a tool so that the effective knowledge sources get high priorities to be invoked, (v) the organization of a knowledge source which allows the image analysis related knowledge sources to be reapplied on unsatisfactory initial results, and (vi) an evidence combination scheme to combine confidence values associated with pieces of evidence generated by various knowledge sources. An address block location system (ABLS) is developed and implemented in accordance with this framework and shown to be capable of dealing with a wide range of environments: from those having a high degree of global spatial structure (e.g., letter mail envelopes which conform to specifications) to those with no structure (e.g., magazines with randomly pasted address labels). Experimental results with a database of difficult cases demonstrating the promise of the computational framework are presented.