Letter to D. A. Whedon. Pittsfield, April 30, 1845.

1845 handwritten letter from Daniel Denison Whedon to Daniel A. Whedon.

The journal of the Bishop of Montreal the Church Missionary Society's North-west America Mission. To which is added, by the secretaries, an appendix, giving an account of the formation of the mission, and its progress to the present time.

http://www.archive.org/details/bishopofmontreal00mounuoft

In the Ojibway country : a story of early missions on the Minnesota frontier

http://www.archive.org/details/inojibwaycountry00scheiala

The African slave trade / by Thomas Fowell Buxton.

Digitized by Google

A brief history of the Bhopal principality in Central India : from the period of its foundation, about one hundred and fifty years ago, to the present time.

http://www.archive.org/details/briefhistoryofth014373mbp

Memoir of Mrs. Sarah L. Huntington Smith, late of the American mission in Syria / by Edward W. Hooker.

http://www.archive.org/details/memoirofhuntingt00hookuoft

Life of St. Vincent of Paul, founder of the Congregation of the Mission and of the Sisters of Charity / M. Collet... ; translated from the French by a Catholic clergyman.

http://www.archive.org/details/lifeofstvincento00colluoft

Deformable Shape Detection and Description via Model-Based Region Grouping

A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with adjacent objects or shadows. The formulation can be used to group image regions based on any image homogeneity predicate; e.g., texture, color, or motion. The recovered shape models can be used directly in object recognition. Experiments with color imagery are reported.

Online and Offline Character Recognition Using Alignment to Prototypes

Nearest neighbor classifiers are simple to implement, yet they can model complex non-parametric distributions, and provide state-of-the-art recognition accuracy in OCR databases. At the same time, they may be too slow for practical character recognition, especially when they rely on similarity measures that require computationally expensive pairwise alignments between characters. This paper proposes an efficient method for computing an approximate similarity score between two characters based on their exact alignment to a small number of prototypes. The proposed method is applied to both online and offline character recognition, where similarity is based on widely used and computationally expensive alignment methods, i.e., Dynamic Time Warping and the Hungarian method respectively. In both cases significant recognition speedup is obtained at the expense of only a minor increase in recognition error.